Collate CPUE data
Max Lindmark
13 December, 2021
Intro
In this script, I load exchange data from datras and calculate catch of cod and flounder in unit kg/km^2 (with TVL gear), by correcting for gear dimensions, sweeplength and trawl speed, following Orio et al 2017. I also add oxygen, temperature and depth covariates, which I use for modelling this biomass index. I do this for Q1 and Q4. I use Q4 for the condition data. For the condition data, I also need the environmental covariates. Hence, the study is limited to 2019. For other analyses, I need Q1, and don’t need all envi. covariates, and I have stomach data incl. 2020, hence I need to standardize all trawl data available from Datras.
Load libraries
rm(list = ls())
library(tidyverse); theme_set(theme_light(base_size = 12))
library(readxl)
library(tidylog)
library(RCurl)
library(viridis)
library(RColorBrewer)
library(patchwork)
library(janitor)
library(icesDatras)
library(mapdata)
library(patchwork)
library(rgdal)
library(raster)
library(sf)
library(rgeos)
library(chron)
library(lattice)
library(ncdf4)
library(marmap)
library(rnaturalearth)
library(rnaturalearthdata)
library(mapplots)
library(geosphere)
#remotes::install_github("pbs-assess/sdmTMB")
library(sdmTMB)
#library(gganimate)
world <- ne_countries(scale = "medium", returnclass = "sf")For maps
# Specify map ranges
ymin = 54; ymax = 58; xmin = 12; xmax = 22
map_data <- rnaturalearth::ne_countries(
scale = "medium",
returnclass = "sf", continent = "europe")
# Crop the polygon for plotting and efficiency:
# st_bbox(map_data) # find the rough coordinates
swe_coast <- suppressWarnings(suppressMessages(
st_crop(map_data,
c(xmin = xmin, ymin = ymin, xmax = xmax, ymax = ymax))))
# Transform our map into UTM 33 coordinates, which is the equal-area projection we fit in:
utm_zone33 <- 32633
swe_coast_proj <- sf::st_transform(swe_coast, crs = utm_zone33)
#ggplot(swe_coast_proj) + geom_sf() Read data
# Data were read in from getDATRAS on 2021.10.13
# Read HH data
# bits_hh <- getDATRAS(record = "HH", survey = "BITS", years = 1991:2020, quarters = c(1, 4))
# write.csv(bits_hh, "data/DATRAS_exchange/bits_hh.csv")
bits_hh <- read.csv("data/DATRAS_exchange/bits_hh.csv")
# Read HL data
# bits_hl <- getDATRAS(record = "HL", survey = "BITS", years = 1991:2020, quarters = c(1, 4))
# write.csv(bits_hl, "data/DATRAS_exchange/bits_hl.csv")
bits_hl <- read.csv("data/DATRAS_exchange/bits_hl.csv")
# Read CA data
# bits_ca <- getDATRAS(record = "CA", survey = "BITS", years = 1991:2020, quarters = c(1, 4))
# write.csv(bits_ca, "data/DATRAS_exchange/bits_ca.csv")
bits_ca <- read.csv("data/DATRAS_exchange/bits_ca.csv")
# Read gear standardization data
#sweep <- read.csv("data/from_ale/sweep_9116.csv", sep = ";", dec = ",", fileEncoding = "latin1")
sweep <- read.csv("data/from_ale/sweep_9118_ml.csv", sep = ";", fileEncoding = "latin1")Standardize catch data
Standardize ships
# Before creating a a new ID, make sure that countries and ships names use the same format
sort(unique(sweep$Ship))
#> [1] "26HF" "ATL" "ATLD" "BAL" "BALL" "BPE" "CEV" "CLP" "CLV" "COML"
#> [11] "DAN2" "DANS" "DAR" "GDY" "HAF" "KOH" "KOOT" "MON" "MONL" "SOL"
#> [21] "SOL2" "VSH" "ZBA"
sort(unique(bits_hh$Ship))
#> [1] "06JR" "06S1" "06SL" "26D4" "26HF" "26HI" "67BC" "77AR" "77MA" "77SE"
#> [11] "90MX" "AA36" "ESLF" "ESOR" "ESTM" "LAIZ" "LTDA" "RUEK" "RUJB" "RUNT"
#> [21] "RUS6"
sort(unique(bits_hl$Ship))
#> [1] "06JR" "06S1" "06SL" "26D4" "26HF" "26HI" "67BC" "77AR" "77MA" "77SE"
#> [11] "90MX" "AA36" "ESLF" "ESOR" "ESTM" "LAIZ" "LTDA" "RUEK" "RUJB" "RUNT"
#> [21] "RUS6"
# Change back to the old Ship name standard...
# https://vocab.ices.dk/?ref=315
# https://vocab.ices.dk/?ref=315
# Assumptions:
# SOL is Solea on ICES links above, and SOL1 is the older one of the two SOLs (1 and 2)
# DAN is Dana
# sweep %>% filter(Ship == "DANS") %>% distinct(Year, Country)
# sweep %>% filter(Ship == "DAN2") %>% distinct(Year)
# bits_hh %>% filter(Ship == "67BC") %>% distinct(Year, Country)
# sweep %>% filter(Ship == "DAN2") %>% distinct(Year)
# bits_hh %>% filter(Ship == "26D4") %>% distinct(Year) # Strange that 26DF doesn't extend far back. Which ship did the Danes use? Ok, I have no Danish data that old.
# bits_hh %>% filter(Country == "DK") %>% distinct(Year)
bits_hh <- bits_hh %>%
mutate(Ship2 = fct_recode(Ship,
"SOL" = "06S1",
"SOL2" = "06SL",
"DAN2" = "26D4",
"HAF" = "26HF",
"HAF" = "26HI",
"HAF" = "67BC",
"BAL" = "67BC",
"ARG" = "77AR",
"77SE" = "77SE",
"AA36" = "AA36",
"KOOT" = "ESLF",
"KOH" = "ESTM",
"DAR" = "LTDA",
"ATLD" = "RUJB",
"ATL" = "RUNT"),
Ship2 = as.character(Ship2)) %>%
mutate(Ship3 = ifelse(Country == "LV" & Ship2 == "BAL", "BALL", Ship2))
bits_hl <- bits_hl %>%
mutate(Ship2 = fct_recode(Ship,
"SOL" = "06S1",
"SOL2" = "06SL",
"DAN2" = "26D4",
"HAF" = "26HF",
"HAF" = "26HI",
"HAF" = "67BC",
"BAL" = "67BC",
"ARG" = "77AR",
"77SE" = "77SE",
"AA36" = "AA36",
"KOOT" = "ESLF",
"KOH" = "ESTM",
"DAR" = "LTDA",
"ATLD" = "RUJB",
"ATL" = "RUNT"),
Ship2 = as.character(Ship2)) %>%
mutate(Ship3 = ifelse(Country == "LV" & Ship2 == "BAL", "BALL", Ship2))
bits_ca <- bits_ca %>%
mutate(Ship2 = fct_recode(Ship,
"SOL" = "06S1",
"SOL2" = "06SL",
"DAN2" = "26D4",
"HAF" = "26HF",
"HAF" = "26HI",
"HAF" = "67BC",
"BAL" = "67BC",
"ARG" = "77AR",
"77SE" = "77SE",
"AA36" = "AA36",
"KOOT" = "ESLF",
"KOH" = "ESTM",
"DAR" = "LTDA",
"ATLD" = "RUJB",
"ATL" = "RUNT"),
Ship2 = as.character(Ship2)) %>%
mutate(Ship3 = ifelse(Country == "LV" & Ship2 == "BAL", "BALL", Ship2))
# Ok, which ships are missing in the exchange data?
unique(bits_hh$Ship3)[!unique(bits_hh$Ship3) %in% unique(sweep$Ship)]
#> [1] "AA36" "90MX" "ARG" "06JR" "LAIZ" "RUEK" "RUS6" "77MA" "77SE" "ESOR"
# Swedish Ships and unidentified ships are NOT in the Sweep data
unique(sweep$Ship3)[!unique(sweep$Ship3) %in% unique(bits_hh$Ship3)]
#> NULL
# But all Sweep Ships are in the exchange dataStandardize countries
# Now check which country codes are used
sort(unique(sweep$Country))
#> [1] "DEN" "EST" "GFR" "LAT" "LTU" "POL" "RUS" "SWE"
sort(unique(bits_hh$Country))
#> [1] "DE" "DK" "EE" "LT" "LV" "PL" "RU" "SE"
# https://www.nationsonline.org/oneworld/country_code_list.htm#E
bits_hh <- bits_hh %>%
mutate(Country = fct_recode(Country,
"DEN" = "DK",
"EST" = "EE",
"GFR" = "DE",
"LAT" = "LV",
"LTU" = "LT",
"POL" = "PL",
"RUS" = "RU",
"SWE" = "SE"),
Country = as.character(Country))
bits_hl <- bits_hl %>%
mutate(Country = fct_recode(Country,
"DEN" = "DK",
"EST" = "EE",
"GFR" = "DE",
"LAT" = "LV",
"LTU" = "LT",
"POL" = "PL",
"RUS" = "RU",
"SWE" = "SE"),
Country = as.character(Country))
bits_ca <- bits_ca %>%
mutate(Country = fct_recode(Country,
"DEN" = "DK",
"EST" = "EE",
"GFR" = "DE",
"LAT" = "LV",
"LTU" = "LT",
"POL" = "PL",
"RUS" = "RU",
"SWE" = "SE"),
Country = as.character(Country))
# Gear? Are they the same?
sort(unique(bits_hh$Gear))
#> [1] "CAM" "CHP" "DT" "EGY" "ESB" "EXP" "FOT" "GOV" "GRT" "H20" "HAK" "LBT"
#> [13] "P20" "PEL" "SON" "TVL" "TVS"
sort(unique(bits_hl$Gear))
#> [1] "CAM" "CHP" "DT" "EGY" "ESB" "EXP" "FOT" "GOV" "GRT" "H20" "HAK" "LBT"
#> [13] "P20" "PEL" "SON" "TVL" "TVS"
sort(unique(sweep$Gear))
#> [1] "CAM" "CHP" "DT" "EGY" "ESB" "EXP" "GRT" "H20" "HAK" "LBT" "LPT" "P20"
#> [13] "PEL" "SON" "TVL" "TVS"
# Which gears are NOT in the sweep data?
unique(bits_hl$Gear)[!unique(bits_hl$Gear) %in% unique(sweep$Gear)]
#> [1] "FOT" "GOV"Create a simple ID that works across all exchange data
# Create ID column
bits_ca <- bits_ca %>%
mutate(IDx = paste(Year, Quarter, Country, Ship, Gear, StNo, HaulNo, sep = "."))
bits_hl <- bits_hl %>%
mutate(IDx = paste(Year, Quarter, Country, Ship, Gear, StNo, HaulNo, sep = "."))
bits_hh <- bits_hh %>%
mutate(IDx = paste(Year, Quarter, Country, Ship, Gear, StNo, HaulNo, sep = "."))
# Works like a haul-id
bits_hh %>% group_by(IDx) %>% mutate(n = n()) %>% ungroup() %>% distinct(n)
#> # A tibble: 1 × 1
#> n
#> <int>
#> 1 1Create the same unique haul-ID in the cpue data that I have in the sweep-file
bits_hl <- bits_hl %>%
mutate(haul.id = paste(Year, Quarter, Country, Ship3, Gear, StNo, HaulNo, sep = ":"))
bits_hh <- bits_hh %>%
mutate(haul.id = paste(Year, Quarter, Country, Ship3, Gear, StNo, HaulNo, sep = ":"))
bits_hh %>% group_by(haul.id) %>% mutate(n = n()) %>% ungroup() %>% distinct(n)
#> # A tibble: 1 × 1
#> n
#> <int>
#> 1 1Clean DATRAS EXCHANGE data
# Select just valid, additional and no oxygen hauls
bits_hh <- bits_hh %>%
#filter(!Country == "SWE") %>% # I'll deal with Sweden later...
filter(HaulVal %in% c("A","N","V"))
# Add ICES rectangle
bits_hh$Rect <- mapplots::ices.rect2(lon = bits_hh$ShootLong, lat = bits_hh$ShootLat)
# Add ICES subdivisions
shape <- shapefile("data/ICES_StatRec_mapto_ICES_Areas/StatRec_map_Areas_Full_20170124.shp")
pts <- SpatialPoints(cbind(bits_hh$ShootLong, bits_hh$ShootLat),
proj4string = CRS(proj4string(shape)))
#> Warning in proj4string(shape): CRS object has comment, which is lost in output
bits_hh$sub_div <- over(pts, shape)$Area_27
# Rename subdivisions to the more common names and do some more filtering (by sub div and area)
sort(unique(bits_hh$sub_div))
#> [1] "3.a.20" "3.a.21" "3.b.23" "3.c.22" "3.d.24" "3.d.25"
#> [7] "3.d.26" "3.d.27" "3.d.28.1" "3.d.28.2" "3.d.29"
bits_hh <- bits_hh %>%
mutate(sub_div = factor(sub_div),
sub_div = fct_recode(sub_div,
"20" = "3.a.20",
"21" = "3.a.21",
"22" = "3.c.22",
"23" = "3.b.23",
"24" = "3.d.24",
"25" = "3.d.25",
"26" = "3.d.26",
"27" = "3.d.27",
"28" = "3.d.28.1",
"28" = "3.d.28.2",
"29" = "3.d.29"),
sub_div = as.character(sub_div))
# Now add the fishing line information from the sweep file (we need that later
# to standardize based on gear geometry). We add in the in the HH data and then
# transfer it to the other exchange data files when left_joining.
# Check which Fishing lines I have in the sweep data:
fishing_line <- sweep %>% group_by(Gear) %>% distinct(Fishing.line)
bits_hh <- left_join(bits_hh, fishing_line)
# sweep %>% group_by(Gear) %>% distinct(Fishing.line)
# bits_hh %>% group_by(Gear) %>% distinct(Fishing.line)
bits_hh$Fishing.line <- as.numeric(bits_hh$Fishing.line)
# Which gears do now have fishing line?
bits_hh$Fishing.line[is.na(bits_hh$Fishing.line)] <- -9
bits_hh %>% filter(Fishing.line == -9) %>% distinct(Gear)
#> Gear
#> 1 GRT
#> 2 FOT
#> 3 GOV
#> 4 EXP
#> 5 CAM
#> 6 EGY
#> 7 DT
#> 8 ESB
#> 9 HAK
# 1 GRT
# 2 CAM
# 3 EXP
# 4 FOT
# 5 GOV
# 6 EGY
# 7 DT
# 8 ESB
# 9 HAK
# FROM the index files (Orio, "Research Östersjön 2")
# FOT has 83
# GOV has 160
# ESB ??
# GRT ??
# Rest are unknown and likely not used by swedish data (therefore their correction
# factors my be in the sweep file)
# Add these values:
bits_hh <- bits_hh %>% mutate(Fishing.line = ifelse(Gear == "FOT", 83, Fishing.line))
bits_hh <- bits_hh %>% mutate(Fishing.line = ifelse(Gear == "GOV", 160, Fishing.line))
# Now select the hauls in the HH data when subsetting the HL data
bits_hl <- bits_hl %>%
filter(haul.id %in% bits_hh$haul.id)
# Match columns from the HH data to the HL and CA data
sort(unique(bits_hh$sub_div))
#> [1] "20" "21" "22" "23" "24" "25" "26" "27" "28" "29"
sort(colnames(bits_hh))
#> [1] "BotCurDir" "BotCurSpeed" "BotSal"
#> [4] "BotTemp" "Buoyancy" "BySpecRecCode"
#> [7] "CodendMesh" "Country" "DataType"
#> [10] "DateofCalculation" "Day" "DayNight"
#> [13] "Depth" "DepthStratum" "Distance"
#> [16] "DoorSpread" "DoorSurface" "DoorType"
#> [19] "DoorWgt" "Fishing.line" "Gear"
#> [22] "GearEx" "GroundSpeed" "haul.id"
#> [25] "HaulDur" "HaulLat" "HaulLong"
#> [28] "HaulNo" "HaulVal" "HydroStNo"
#> [31] "IDx" "KiteDim" "MaxTrawlDepth"
#> [34] "MinTrawlDepth" "Month" "Netopening"
#> [37] "PelSampType" "Quarter" "RecordType"
#> [40] "Rect" "Rigging" "SecchiDepth"
#> [43] "Ship" "Ship2" "Ship3"
#> [46] "ShootLat" "ShootLong" "SpeedWater"
#> [49] "StatRec" "StdSpecRecCode" "StNo"
#> [52] "sub_div" "SurCurDir" "SurCurSpeed"
#> [55] "SurSal" "SurTemp" "Survey"
#> [58] "SweepLngt" "SwellDir" "SwellHeight"
#> [61] "ThClineDepth" "ThermoCline" "Tickler"
#> [64] "TidePhase" "TideSpeed" "TimeShot"
#> [67] "TowDir" "Turbidity" "WarpDen"
#> [70] "Warpdia" "Warplngt" "WgtGroundRope"
#> [73] "WindDir" "WindSpeed" "WingSpread"
#> [76] "X" "Year"
bits_hh_merge <- bits_hh %>%
dplyr::select(sub_div, Rect, HaulVal, StdSpecRecCode, BySpecRecCode, Fishing.line,
DataType, HaulDur, GroundSpeed, haul.id, IDx, ShootLat, ShootLong)
bits_hl <- left_join(dplyr::select(bits_hl, -haul.id), bits_hh_merge, by = "IDx")
bits_ca <- left_join(bits_ca, bits_hh_merge, by = "IDx")
# Now filter the subdivisions I want from all data sets
bits_hh <- bits_hh %>% filter(sub_div %in% c(24, 25, 26, 27, 28))
bits_hl <- bits_hl %>% filter(sub_div %in% c(24, 25, 26, 27, 28))
bits_ca <- bits_ca %>% filter(sub_div %in% c(24, 25, 26, 27, 28))Filter species
hlcod <- bits_hl %>%
filter(SpecCode %in% c("126436", "164712")) %>%
mutate(Species = "Gadus morhua")
hlfle <- bits_hl %>%
filter(SpecCode %in% c("127141", "172894")) %>%
mutate(Species = "Platichthys flesus")Prepare to add 0 catches
# Find common columns in the HH and HL data (here already subset by species)
comcol <- intersect(names(hlcod), names(bits_hh))
# What is the proportion of zero-catch hauls?
# Here we don't have zero catches
hlcod %>%
group_by(haul.id, Year) %>%
summarise(CPUEun_haul = sum(HLNoAtLngt)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
distinct(zero_catch)
#> # A tibble: 1 × 1
#> zero_catch
#> <chr>
#> 1 N
# Cod: Add 0s and then remove lines with SpecVal = 0 (first NA because we don't have a match in the HH, then make them 0 later)
hlcod0 <- full_join(hlcod, bits_hh[, comcol], by = comcol)
# No zeroes yet
hlcod0 %>%
group_by(haul.id, Year) %>%
summarise(CPUEun_haul = sum(HLNoAtLngt)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
distinct(zero_catch)
#> # A tibble: 1 × 1
#> zero_catch
#> <lgl>
#> 1 NA
hlcod0$SpecVal[is.na(hlcod0$SpecVal)] <- "zeroCatch"
hlcod0$SpecVal <- factor(hlcod0$SpecVal)
hlcod0 <- hlcod0 %>% filter(!SpecVal == "0")
# Add species again after merge
hlcod0$Species<-"Gadus morhua"
# Flounder: Add 0s, remove them if StdSpecRecCode !=1 and then remove lines with SpecVal = 0
hlfle0 <- full_join(hlfle, bits_hh[, comcol], by = comcol)
hlfle0 <- hlfle0[!(is.na(hlfle0$Species) & hlfle0$StdSpecRecCode != 1),]
hlfle0$SpecVal[is.na(hlfle0$SpecVal)] <- "zeroCatch"
hlfle0$SpecVal <- factor(hlfle0$SpecVal)
hlfle0 <- hlfle0 %>% filter(!SpecVal == "0")
hlfle0$Species<-"Platichthys flesus"
# Check number of hauls per species
hlcod0 %>% distinct(haul.id) %>% nrow()
#> [1] 12488
hlfle0 %>% distinct(haul.id) %>% nrow()
#> [1] 12214Create (unstandardized) CPUE for SpecVal=1. If DataType=C then CPUEun=HLNoAtLngt, if DataType=R then CPUEun=HLNoAtLngt/(HaulDur/60), if DataType=S then CPUEun=(HLNoAtLngt*SubFactor)/(HaulDur/60). If SpecVal="zeroCatch" then CPUEun=0, if SpecVal=4 we need to decide (no length measurements, only total catch). Note that here we also add zero CPUE if SpecVal=="zeroCatch".
Then I will sum for the same haul the CPUE of the same length classes if they were sampled with different subfactors or with different sexes.
# Cod
hlcod0 <- hlcod0 %>%
mutate(CPUEun = ifelse(SpecVal == "1" & DataType == "C",
HLNoAtLngt,
ifelse(SpecVal == "1" & DataType == "R",
HLNoAtLngt/(HaulDur/60),
ifelse(SpecVal == "1" & DataType == "S",
(HLNoAtLngt*SubFactor)/(HaulDur/60),
ifelse(SpecVal == "zeroCatch", 0, NA)))))
# Plot and fill by zero catch
hlcod0 %>%
group_by(haul.id, Year) %>%
summarise(CPUEun_haul = sum(CPUEun)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
group_by(Year, zero_catch) %>%
summarise(n = n()) %>%
ggplot(., aes(x = Year, y = n, fill = zero_catch)) +
geom_bar(stat = "identity")
# Some rows have multiple rows per combination of length class and haul id,
# so we need to sum it up
hlcod0 %>% group_by(LngtClass, haul.id) %>% mutate(n = n()) %>% ungroup() %>% distinct(n)
#> # A tibble: 2 × 1
#> n
#> <int>
#> 1 1
#> 2 2
hlcod0 %>% group_by(LngtClass, haul.id) %>% mutate(n = n()) %>% ungroup() %>% filter(n == 2) %>% as.data.frame() %>% head(20)
#> X RecordType Survey Quarter Country Ship Gear SweepLngt GearEx DoorType
#> 1 6847 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 2 13793 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 3 13988 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 4 58045 HL BITS 1 LAT LAIZ LBT NA <NA> NA
#> 5 205495 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 6 300422 HL BITS 4 EST ESLF TVS NA <NA> NA
#> 7 300423 HL BITS 4 EST ESLF TVS NA <NA> NA
#> 8 325369 HL BITS 4 DEN 26D4 TVL NA R NA
#> 9 325375 HL BITS 4 DEN 26D4 TVL NA R NA
#> 10 326062 HL BITS 4 DEN 26D4 TVL NA R NA
#> 11 326064 HL BITS 4 DEN 26D4 TVL NA R NA
#> 12 326065 HL BITS 4 DEN 26D4 TVL NA R NA
#> 13 326066 HL BITS 4 DEN 26D4 TVL NA R NA
#> 14 326067 HL BITS 4 DEN 26D4 TVL NA R NA
#> 15 326068 HL BITS 4 DEN 26D4 TVL NA R NA
#> 16 326069 HL BITS 4 DEN 26D4 TVL NA R NA
#> 17 326071 HL BITS 4 DEN 26D4 TVL NA R NA
#> 18 326073 HL BITS 4 DEN 26D4 TVL NA R NA
#> 19 326077 HL BITS 4 DEN 26D4 TVL NA R NA
#> 20 326079 HL BITS 4 DEN 26D4 TVL NA R NA
#> StNo HaulNo Year SpecCodeType SpecCode SpecVal Sex TotalNo CatIdentifier
#> 1 000001 5 1991 W 126436 4 <NA> 3 1
#> 2 000003 33 1991 W 126436 4 <NA> 6 1
#> 3 000003 29 1991 W 126436 4 <NA> 183 1
#> 4 000001 23 1993 W 126436 4 <NA> 1 1
#> 5 <NA> 10 1998 T 164712 4 <NA> -9 1
#> 6 14 14 2000 T 164712 1 M 2 1
#> 7 14 14 2000 T 164712 1 F 4 1
#> 8 63 31 2001 T 164712 1 M 5 1
#> 9 63 31 2001 T 164712 1 F 7 1
#> 10 83 37 2001 T 164712 1 M 21 1
#> 11 83 37 2001 T 164712 1 M 21 1
#> 12 83 37 2001 T 164712 1 M 21 1
#> 13 83 37 2001 T 164712 1 M 21 1
#> 14 83 37 2001 T 164712 1 M 21 1
#> 15 83 37 2001 T 164712 1 M 21 1
#> 16 83 37 2001 T 164712 1 M 21 1
#> 17 83 37 2001 T 164712 1 M 21 1
#> 18 83 37 2001 T 164712 1 M 21 1
#> 19 83 37 2001 T 164712 1 F 42 1
#> 20 83 37 2001 T 164712 1 F 42 1
#> NoMeas SubFactor SubWgt CatCatchWgt LngtCode LngtClass HLNoAtLngt DevStage
#> 1 NA 1 NA NA <NA> NA -9 <NA>
#> 2 NA 1 NA NA <NA> NA -9 <NA>
#> 3 NA 1 NA NA <NA> NA -9 <NA>
#> 4 NA 1 NA NA <NA> NA -9 <NA>
#> 5 NA 1 NA NA <NA> NA -9 <NA>
#> 6 3 1 NA 32 1 35 2 <NA>
#> 7 3 1 NA 32 1 35 2 <NA>
#> 8 5 1 NA 3142 1 22 2 <NA>
#> 9 7 1 NA 3142 1 22 1 <NA>
#> 10 21 1 NA 64261 1 22 1 <NA>
#> 11 21 1 NA 64261 1 38 2 <NA>
#> 12 21 1 NA 64261 1 39 2 <NA>
#> 13 21 1 NA 64261 1 41 1 <NA>
#> 14 21 1 NA 64261 1 42 1 <NA>
#> 15 21 1 NA 64261 1 44 2 <NA>
#> 16 21 1 NA 64261 1 45 4 <NA>
#> 17 21 1 NA 64261 1 48 2 <NA>
#> 18 21 1 NA 64261 1 52 1 <NA>
#> 19 42 1 NA 64261 1 22 1 <NA>
#> 20 42 1 NA 64261 1 38 2 <NA>
#> LenMeasType DateofCalculation Valid_Aphia Ship2 Ship3
#> 1 NA 20211203 126436 90MX 90MX
#> 2 NA 20211203 126436 90MX 90MX
#> 3 NA 20211203 126436 90MX 90MX
#> 4 NA 20211203 126436 LAIZ LAIZ
#> 5 NA 20140617 126436 ATLD ATLD
#> 6 NA 20131112 126436 KOOT KOOT
#> 7 NA 20131112 126436 KOOT KOOT
#> 8 NA 20131113 126436 DAN2 DAN2
#> 9 NA 20131113 126436 DAN2 DAN2
#> 10 NA 20131113 126436 DAN2 DAN2
#> 11 NA 20131113 126436 DAN2 DAN2
#> 12 NA 20131113 126436 DAN2 DAN2
#> 13 NA 20131113 126436 DAN2 DAN2
#> 14 NA 20131113 126436 DAN2 DAN2
#> 15 NA 20131113 126436 DAN2 DAN2
#> 16 NA 20131113 126436 DAN2 DAN2
#> 17 NA 20131113 126436 DAN2 DAN2
#> 18 NA 20131113 126436 DAN2 DAN2
#> 19 NA 20131113 126436 DAN2 DAN2
#> 20 NA 20131113 126436 DAN2 DAN2
#> IDx sub_div Rect HaulVal StdSpecRecCode
#> 1 1991.1.LAT.90MX.LBT.000001.5 28 43H1 V 1
#> 2 1991.1.LAT.90MX.LBT.000003.33 28 43H0 V 1
#> 3 1991.1.LAT.90MX.LBT.000003.29 28 43H0 V 1
#> 4 1993.1.LAT.LAIZ.LBT.000001.23 28 43H1 V 1
#> 5 1998.1.RUS.RUJB.HAK.NA.10 26 38G9 V 1
#> 6 2000.4.EST.ESLF.TVS.14.14 28 45H1 V 1
#> 7 2000.4.EST.ESLF.TVS.14.14 28 45H1 V 1
#> 8 2001.4.DEN.26D4.TVL.63.31 26 39G8 V 1
#> 9 2001.4.DEN.26D4.TVL.63.31 26 39G8 V 1
#> 10 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 11 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 12 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 13 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 14 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 15 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 16 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 17 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 18 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 19 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 20 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> BySpecRecCode Fishing.line DataType HaulDur GroundSpeed
#> 1 1 28.00 C 40 -9.0
#> 2 1 28.00 C 30 -9.0
#> 3 1 28.00 C 20 -9.0
#> 4 1 28.00 C 60 -9.0
#> 5 1 -9.00 C 30 3.8
#> 6 1 33.22 C 30 3.0
#> 7 1 33.22 C 30 3.0
#> 8 1 63.46 R 30 3.0
#> 9 1 63.46 R 30 3.0
#> 10 1 63.46 R 31 3.1
#> 11 1 63.46 R 31 3.1
#> 12 1 63.46 R 31 3.1
#> 13 1 63.46 R 31 3.1
#> 14 1 63.46 R 31 3.1
#> 15 1 63.46 R 31 3.1
#> 16 1 63.46 R 31 3.1
#> 17 1 63.46 R 31 3.1
#> 18 1 63.46 R 31 3.1
#> 19 1 63.46 R 31 3.1
#> 20 1 63.46 R 31 3.1
#> haul.id ShootLat ShootLong Species CPUEun n
#> 1 1991:1:LAT:90MX:LBT:000001:5 57.3833 21.3000 Gadus morhua NA 2
#> 2 1991:1:LAT:90MX:LBT:000003:33 57.2167 20.7000 Gadus morhua NA 2
#> 3 1991:1:LAT:90MX:LBT:000003:29 57.1500 20.6500 Gadus morhua NA 2
#> 4 1993:1:LAT:LAIZ:LBT:000001:23 57.3000 21.2333 Gadus morhua NA 2
#> 5 1998:1:RUS:ATLD:HAK:NA:10 54.6333 19.6500 Gadus morhua NA 2
#> 6 2000:4:EST:KOOT:TVS:14:14 58.0167 21.0833 Gadus morhua 2.000000 2
#> 7 2000:4:EST:KOOT:TVS:14:14 58.0167 21.0833 Gadus morhua 2.000000 2
#> 8 2001:4:DEN:DAN2:TVL:63:31 55.4699 18.3116 Gadus morhua 4.000000 2
#> 9 2001:4:DEN:DAN2:TVL:63:31 55.4699 18.3116 Gadus morhua 2.000000 2
#> 10 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.935484 2
#> 11 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 3.870968 2
#> 12 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 3.870968 2
#> 13 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.935484 2
#> 14 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.935484 2
#> 15 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 3.870968 2
#> 16 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 7.741935 2
#> 17 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 3.870968 2
#> 18 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.935484 2
#> 19 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.935484 2
#> 20 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 3.870968 2
test <- hlcod0 %>% group_by(LngtClass, haul.id) %>% mutate(n = n()) %>% ungroup() %>% filter(n == 2)
test_id <- test$haul.id[2]
hlcodL <- hlcod0 %>%
group_by(LngtClass, haul.id) %>%
mutate(CPUEun = sum(CPUEun)) %>%
ungroup() %>%
mutate(id3 = paste(haul.id, LngtClass)) %>%
distinct(id3, .keep_all = TRUE) %>%
dplyr::select(-X, -id3) # Clean up a bit
# Check with an ID
# filter(hlcod0, haul.id == test_id)
# filter(hlcodL, haul.id == test_id) %>% as.data.frame()
# Do we still have 0 catches?
hlcodL %>%
group_by(haul.id, Year) %>%
summarise(CPUEun_haul = sum(CPUEun)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
group_by(Year, zero_catch) %>%
summarise(n = n()) %>%
ggplot(., aes(x = Year, y = n, fill = zero_catch)) +
geom_bar(stat = "identity")
# Flounder
hlfle0 <- hlfle0 %>%
mutate(CPUEun = ifelse(SpecVal == "1" & DataType == "C",
HLNoAtLngt,
ifelse(SpecVal == "1" & DataType == "R",
HLNoAtLngt/(HaulDur/60),
ifelse(SpecVal == "1" & DataType == "S",
(HLNoAtLngt*SubFactor)/(HaulDur/60),
ifelse(SpecVal == "zeroCatch", 0, NA)))))
# Sum up the CPUES if multiple per length class and haul
hlfleL <- hlfle0 %>%
group_by(LngtClass, haul.id) %>%
mutate(CPUEun = sum(CPUEun)) %>%
ungroup() %>%
mutate(id3 = paste(haul.id, LngtClass)) %>%
distinct(id3, .keep_all = TRUE) %>%
dplyr::select(-X, -id3)Get and add annual weight-length relationships from the CA data for both cod and flounder so that I can calculate CPUE in biomass rather than numbers further down
# Cod
bits_ca_cod <- bits_ca %>%
filter(SpecCode %in% c("164712", "126436")) %>%
mutate(StNo = as.numeric(StNo)) %>%
mutate(Species = "Cod") %>%
mutate(ID = paste(Year, Quarter, Country, Ship, Gear, StNo, HaulNo, sep = "."))
#> Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
# Now I need to copy rows with NoAtLngt > 1 so that 1 row = 1 ind
# First make a small test
# nrow(bits_ca_cod)
# test_id <- head(filter(bits_ca_cod, CANoAtLngt == 5))$ID[1]
# filter(bits_ca_cod, ID == test_id & CANoAtLngt == 5)
bits_ca_cod <- bits_ca_cod %>% map_df(., rep, .$CANoAtLngt)
# head(data.frame(filter(bits_ca_cod, ID == test_id & CANoAtLngt == 5)), 20)
# nrow(bits_ca_cod)
# Looks ok!
# Standardize length and drop NA weights (need that for condition)
bits_ca_cod <- bits_ca_cod %>%
drop_na(IndWgt) %>%
drop_na(LngtClass) %>%
filter(IndWgt > 0 & LngtClass > 0) %>% # Filter positive length and weight
mutate(weight_kg = IndWgt/1000) %>%
mutate(length_cm = ifelse(LngtCode == ".",
LngtClass/10,
LngtClass)) # Standardize length ((https://vocab.ices.dk/?ref=18))
# Plot
ggplot(bits_ca_cod, aes(IndWgt, length_cm)) +
geom_point() +
facet_wrap(~Year)
# Now extract the coefficients for each year (not bothering with outliers at the moment)
cod_intercept <- bits_ca_cod %>%
split(.$Year) %>%
purrr::map(~lm(log(IndWgt) ~ log(length_cm), data = .x)) %>%
purrr::map_df(broom::tidy, .id = 'Year') %>%
filter(term == "(Intercept)") %>%
mutate(a = exp(estimate)) %>%
mutate(Year = as.integer(Year)) %>%
dplyr::select(Year, a)
cod_slope <- bits_ca_cod %>%
split(.$Year) %>%
purrr::map(~lm(log(IndWgt) ~ log(length_cm), data = .x)) %>%
purrr::map_df(broom::tidy, .id = 'Year') %>%
filter(term == "log(length_cm)") %>%
mutate(Year = as.integer(Year)) %>%
rename("b" = "estimate") %>%
dplyr::select(Year, b)
# Flounder
bits_ca_fle <- bits_ca %>%
filter(SpecCode %in% c("127141", "172894")) %>%
mutate(StNo = as.numeric(StNo)) %>%
mutate(Species = "Flounder") %>%
mutate(ID = paste(Year, Quarter, Country, Ship, Gear, StNo, HaulNo, sep = "."))
#> Warning in mask$eval_all_mutate(quo): NAs introduced by coercion
bits_ca_fle <- bits_ca_fle %>% map_df(., rep, .$CANoAtLngt)
# Standardize length and drop NA weights (need that for condition)
bits_ca_fle <- bits_ca_fle %>%
drop_na(IndWgt) %>%
drop_na(LngtClass) %>%
filter(IndWgt > 0 & LngtClass > 0) %>% # Filter positive length and weight
mutate(weight_kg = IndWgt/1000) %>%
mutate(length_cm = ifelse(LngtCode == ".",
LngtClass/10,
LngtClass)) %>% # Standardize length ((https://vocab.ices.dk/?ref=18))
mutate(keep = ifelse(LngtCode == "." & Year == 2008, "N", "Y")) %>%
filter(keep == "Y") %>%
filter(length_cm < 70)
# Plot
ggplot(bits_ca_fle, aes(IndWgt, length_cm, color = LngtCode)) +
geom_point() +
facet_wrap(~Year)
# Now extract the coefficients for each year (not bothering with outliers at the moment)
fle_intercept <- bits_ca_fle %>%
split(.$Year) %>%
purrr::map(~lm(log(IndWgt) ~ log(length_cm), data = .x)) %>%
purrr::map_df(broom::tidy, .id = 'Year') %>%
filter(term == "(Intercept)") %>%
mutate(a = exp(estimate)) %>%
mutate(Year = as.integer(Year)) %>%
dplyr::select(Year, a)
fle_slope <- bits_ca_fle %>%
split(.$Year) %>%
purrr::map(~lm(log(IndWgt) ~ log(length_cm), data = .x)) %>%
purrr::map_df(broom::tidy, .id = 'Year') %>%
filter(term == "log(length_cm)") %>%
mutate(Year = as.integer(Year)) %>%
rename("b" = "estimate") %>%
dplyr::select(Year, b)Join the annual L-W relationships to the respective catch data to calculate CPUE in biomass not abundance
# These are the haul-data
# hlcodL
# hlfleL
hlcodL <- left_join(hlcodL, cod_intercept, by = "Year")
hlcodL <- left_join(hlcodL, cod_slope, by = "Year")
hlfleL <- left_join(hlfleL, fle_intercept, by = "Year")
hlfleL <- left_join(hlfleL, fle_slope, by = "Year")Convert from CPUE in numbers to kg
# First standardize length to cm and then check how zero-catches are implemented at this stage
hlcodL <- hlcodL %>%
mutate(length_cm = ifelse(LngtCode == ".",
LngtClass/10,
LngtClass)) # Standardize length ((https://vocab.ices.dk/?ref=18))
filter(hlcodL, length_cm == 0) # No such thing
#> # A tibble: 0 × 49
#> # … with 49 variables: RecordType <chr>, Survey <chr>, Quarter <int>,
#> # Country <chr>, Ship <chr>, Gear <chr>, SweepLngt <int>, GearEx <chr>,
#> # DoorType <lgl>, StNo <chr>, HaulNo <int>, Year <int>, SpecCodeType <chr>,
#> # SpecCode <int>, SpecVal <fct>, Sex <chr>, TotalNo <dbl>,
#> # CatIdentifier <int>, NoMeas <int>, SubFactor <dbl>, SubWgt <int>,
#> # CatCatchWgt <int>, LngtCode <chr>, LngtClass <int>, HLNoAtLngt <dbl>,
#> # DevStage <chr>, LenMeasType <int>, DateofCalculation <int>, …
# Now check if all rows where length is NA are the ones with zero catch!
hlcodL %>%
mutate(length2 = replace_na(length_cm, -9),
no_length = ifelse(length2 < 0, "T", "F")) %>%
ggplot(., aes(length2, CPUEun, color = no_length)) + geom_point(alpha = 0.2) + facet_wrap(~no_length)
#> Warning: Removed 5 rows containing missing values (geom_point).
# Right, so all hauls with zero catch have NA length_cm. I don't have any NA catches
t <- hlcodL %>% drop_na(CPUEun)
t <- hlcodL %>% filter(CPUEun == 0)
t <- hlcodL %>% drop_na(length_cm)
# In other words, a zero catch is when the catch is zero and length_cm is NA
# In order to not get any NA CPUEs in unit biomass because length is NA (I want them instead
# to be 0, as the numbers-CPUE is), I will replace length_cm == NA with length_cm == 0 before
# calculating biomass cpue
hlcodL <- hlcodL %>% mutate(length_cm2 = replace_na(length_cm, 0))
# Standardize length in the haul-data and calculate weight
hlcodL <- hlcodL %>%
mutate(weight_kg = (a*length_cm2^b)/1000) %>%
mutate(CPUEun_kg = weight_kg*CPUEun)
# Plot and check it's correct also in this data
ggplot(hlcodL, aes(weight_kg, length_cm2)) +
geom_point() +
facet_wrap(~Year)
# Hmm, some unrealistic weights actually
hlcodL %>% arrange(desc(weight_kg)) %>% as.data.frame()
#> RecordType Survey Quarter Country Ship Gear SweepLngt GearEx DoorType
#> 1 HL BITS 1 DEN 26D4 GRT NA S NA
#> 2 HL BITS 1 DEN 26D4 GRT NA S NA
#> 3 HL BITS 1 DEN 26D4 GRT NA S NA
#> 4 HL BITS 1 DEN 26D4 GRT NA S NA
#> 5 HL BITS 1 DEN 26D4 GRT NA S NA
#> 6 HL BITS 1 DEN 26D4 GRT NA S NA
#> 7 HL BITS 1 DEN 26D4 GRT NA S NA
#> 8 HL BITS 1 DEN 26D4 GRT NA S NA
#> 9 HL BITS 1 DEN 26D4 GRT NA S NA
#> 10 HL BITS 1 DEN 26D4 GRT NA S NA
#> 11 HL BITS 1 DEN 26D4 GRT NA S NA
#> 12 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 13 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 14 HL BITS 1 DEN 26D4 GRT NA S NA
#> 15 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 16 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 17 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 18 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 19 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 20 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 21 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 22 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 23 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 24 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 25 HL BITS 1 DEN 26D4 GRT NA S NA
#> 26 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 27 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 28 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 29 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 30 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 31 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 32 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 33 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 34 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 35 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 36 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 37 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 38 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 39 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 40 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 41 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 42 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 43 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 44 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 45 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 46 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 47 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 48 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 49 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 50 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 51 HL BITS 1 LAT LAIZ LBT NA <NA> NA
#> 52 HL BITS 4 SWE 77AR FOT 180 <NA> NA
#> 53 HL BITS 4 POL 67BC TVL 75 S NA
#> 54 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 55 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 56 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 57 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 58 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 59 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 60 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 61 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 62 HL BITS 1 DEN 26D4 GRT NA S NA
#> 63 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 64 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 65 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 66 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 67 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 68 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 69 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 70 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 71 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 72 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 73 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 74 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 75 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 76 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 77 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 78 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 79 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 80 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 81 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 82 HL BITS 1 DEN 26D4 GRT NA S NA
#> 83 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 84 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 85 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 86 HL BITS 1 DEN 26D4 GRT NA S NA
#> 87 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 88 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 89 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 90 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 91 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 92 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 93 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 94 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 95 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 96 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 97 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 98 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 99 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 100 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 101 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 102 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 103 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 104 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 105 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 106 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 107 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 108 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 109 HL BITS 1 SWE 77AR TVL 95 <NA> NA
#> 110 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 111 HL BITS 4 POL 67BC TVL 75 S NA
#> 112 HL BITS 4 POL 67BC TVL 75 S NA
#> 113 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 114 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 115 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 116 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 117 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 118 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 119 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 120 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 121 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 122 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 123 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 124 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 125 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 126 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 127 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 128 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 129 HL BITS 4 DEN 26D4 GRT NA S NA
#> 130 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 131 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 132 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 133 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 134 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 135 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 136 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 137 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 138 HL BITS 1 DEN 26D4 TVL NA R NA
#> 139 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 140 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 141 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 142 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 143 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 144 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 145 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 146 HL BITS 4 DEN 26D4 TVL NA R NA
#> 147 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 148 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 149 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 150 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 151 HL BITS 1 DEN 26D4 GRT NA S NA
#> 152 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 153 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 154 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 155 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 156 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 157 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 158 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 159 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 160 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 161 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 162 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 163 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 164 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 165 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 166 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 167 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 168 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 169 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 170 HL BITS 1 DEN 26D4 GRT NA S NA
#> 171 HL BITS 4 DEN 26D4 TVL NA R NA
#> 172 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 173 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 174 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 175 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 176 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 177 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 178 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 179 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 180 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 181 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 182 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 183 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 184 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 185 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 186 HL BITS 1 DEN 26D4 TVL NA R NA
#> 187 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 188 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 189 HL BITS 4 SWE 77AR TVL 75 S TRUE
#> 190 HL BITS 1 DEN 26D4 GRT NA S NA
#> 191 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 192 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 193 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 194 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 195 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 196 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 197 HL BITS 1 DEN 26D4 GRT NA S NA
#> 198 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 199 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 200 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 201 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 202 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 203 HL BITS 1 DEN 26D4 GRT NA S NA
#> 204 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 205 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 206 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 207 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 208 HL BITS 1 DEN 26D4 GRT NA S NA
#> 209 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 210 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 211 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 212 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 213 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 214 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 215 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 216 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 217 HL BITS 4 GFR 06S1 TVS NA <NA> NA
#> 218 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 219 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 220 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 221 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 222 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 223 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 224 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 225 HL BITS 4 RUS RUNT TVL NA <NA> NA
#> 226 HL BITS 1 LAT AA36 LBT NA <NA> NA
#> 227 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 228 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 229 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 230 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 231 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 232 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 233 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 234 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 235 HL BITS 1 DEN 26D4 GRT NA S NA
#> 236 HL BITS 1 DEN 26D4 GRT NA S NA
#> 237 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 238 HL BITS 1 SWE 77MA TVL 95 S NA
#> 239 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 240 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 241 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 242 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 243 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 244 HL BITS 4 GFR 06S1 TVS NA <NA> NA
#> 245 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 246 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 247 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 248 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 249 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 250 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 251 HL BITS 1 DEN 26D4 GRT NA S NA
#> 252 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 253 HL BITS 4 DEN 26D4 TVL NA R NA
#> 254 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 255 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 256 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 257 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 258 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 259 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 260 HL BITS 1 LAT 67BC TVL 75 R TRUE
#> 261 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 262 HL BITS 4 POL 67BC TVL 75 S NA
#> 263 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 264 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 265 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 266 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 267 HL BITS 1 DEN 26D4 GRT NA S NA
#> 268 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 269 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 270 HL BITS 1 DEN 26D4 GRT NA S NA
#> 271 HL BITS 1 DEN 26D4 GRT NA S NA
#> 272 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 273 HL BITS 1 DEN 26D4 TVL NA <NA> NA
#> 274 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 275 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 276 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 277 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 278 HL BITS 1 DEN 26D4 TVL NA R NA
#> 279 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 280 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 281 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 282 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 283 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 284 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 285 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 286 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 287 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 288 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 289 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 290 HL BITS 4 SWE 77AR TVL 95 <NA> NA
#> 291 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 292 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 293 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 294 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 295 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 296 HL BITS 1 DEN 26D4 GRT NA S NA
#> 297 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 298 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 299 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 300 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 301 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 302 HL BITS 1 DEN 26D4 GRT NA S NA
#> 303 HL BITS 4 DEN 26D4 TVL NA R NA
#> 304 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 305 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 306 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 307 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 308 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 309 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 310 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 311 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 312 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 313 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 314 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 315 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 316 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 317 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 318 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 319 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 320 HL BITS 1 DEN 26D4 GRT NA S NA
#> 321 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 322 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 323 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 324 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 325 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 326 HL BITS 1 DEN 26D4 GRT NA S NA
#> 327 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 328 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 329 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 330 HL BITS 1 DEN 26D4 GRT NA S NA
#> 331 HL BITS 4 DEN 26D4 TVL NA R NA
#> 332 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 333 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 334 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 335 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 336 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 337 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 338 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 339 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 340 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 341 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 342 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 343 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 344 HL BITS 4 POL 67BC TVL 75 S NA
#> 345 HL BITS 4 POL 67BC TVL 75 S NA
#> 346 HL BITS 1 DEN 26D4 GRT NA S NA
#> 347 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 348 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 349 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 350 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 351 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 352 HL BITS 1 DEN 26D4 TVL NA R TRUE
#> 353 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 354 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 355 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 356 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 357 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 358 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 359 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 360 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 361 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 362 HL BITS 1 DEN 26D4 GRT NA S NA
#> 363 HL BITS 1 DEN 26D4 GRT NA S NA
#> 364 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 365 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 366 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 367 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 368 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 369 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 370 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 371 HL BITS 1 DEN 26D4 TVL NA R NA
#> 372 HL BITS 4 DEN 26D4 TVL NA R NA
#> 373 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 374 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 375 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 376 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 377 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 378 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 379 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 380 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 381 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 382 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 383 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 384 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 385 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 386 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 387 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 388 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 389 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 390 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 391 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 392 HL BITS 1 DEN 26D4 GRT NA S NA
#> 393 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 394 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 395 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 396 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 397 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 398 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 399 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 400 HL BITS 4 SWE 77AR FOT 100 <NA> NA
#> 401 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 402 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 403 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 404 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 405 HL BITS 1 DEN 26D4 GRT NA S NA
#> 406 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 407 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 408 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 409 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 410 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 411 HL BITS 1 DEN 26D4 GRT NA S NA
#> 412 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 413 HL BITS 1 DEN 26D4 GRT NA S NA
#> 414 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 415 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 416 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 417 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 418 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 419 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 420 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 421 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 422 HL BITS 1 SWE 77AR TVL 60 <NA> NA
#> 423 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 424 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 425 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 426 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 427 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 428 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 429 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 430 HL BITS 4 POL 67BC TVL 75 S NA
#> 431 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 432 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 433 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 434 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 435 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 436 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 437 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 438 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 439 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 440 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 441 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 442 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 443 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 444 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 445 HL BITS 4 DEN 26D4 TVL NA R NA
#> 446 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 447 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 448 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 449 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 450 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 451 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 452 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 453 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 454 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 455 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 456 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 457 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 458 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 459 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 460 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 461 HL BITS 1 DEN 26D4 GRT NA S NA
#> 462 HL BITS 1 DEN 26D4 GRT NA S NA
#> 463 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 464 HL BITS 1 DEN 26D4 GRT NA S NA
#> 465 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 466 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 467 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 468 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 469 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 470 HL BITS 1 DEN 26D4 GRT NA S NA
#> 471 HL BITS 1 DEN 26D4 GRT NA S NA
#> 472 HL BITS 1 DEN 26D4 GRT NA S NA
#> 473 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 474 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 475 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 476 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 477 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 478 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 479 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 480 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 481 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 482 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 483 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 484 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 485 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 486 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 487 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 488 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 489 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 490 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 491 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 492 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 493 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 494 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 495 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 496 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 497 HL BITS 1 DEN 26D4 TVL NA R TRUE
#> 498 HL BITS 4 POL 67BC TVL 75 S NA
#> 499 HL BITS 4 POL 67BC TVL 75 S NA
#> 500 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 501 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 502 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 503 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 504 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 505 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 506 HL BITS 4 SWE 77AR TVL 75 S NA
#> 507 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 508 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 509 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 510 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 511 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 512 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 513 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 514 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 515 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 516 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 517 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 518 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 519 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 520 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 521 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 522 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 523 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 524 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 525 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 526 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 527 HL BITS 4 DEN 26D4 TVL NA R NA
#> 528 HL BITS 4 DEN 26D4 TVL NA R NA
#> 529 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 530 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 531 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 532 HL BITS 1 DEN 26D4 GRT NA S NA
#> 533 HL BITS 1 DEN 26D4 GRT NA S NA
#> 534 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 535 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 536 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 537 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 538 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 539 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 540 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 541 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 542 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 543 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 544 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 545 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 546 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 547 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 548 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 549 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 550 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 551 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 552 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 553 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 554 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 555 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 556 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 557 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 558 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 559 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 560 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 561 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 562 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 563 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 564 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 565 HL BITS 4 POL 67BC TVL 75 S NA
#> 566 HL BITS 4 LAT 67BC TVL 75 R TRUE
#> 567 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 568 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 569 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 570 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 571 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 572 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 573 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 574 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 575 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 576 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 577 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 578 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 579 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 580 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 581 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 582 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 583 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 584 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 585 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 586 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 587 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 588 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 589 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 590 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 591 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 592 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 593 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 594 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 595 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 596 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 597 HL BITS 1 LAT LAIZ LBT NA <NA> NA
#> 598 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 599 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 600 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 601 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 602 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 603 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 604 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 605 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 606 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 607 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 608 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 609 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 610 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 611 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 612 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 613 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 614 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 615 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 616 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 617 HL BITS 1 DEN 26D4 GRT NA S NA
#> 618 HL BITS 1 DEN 26D4 GRT NA S NA
#> 619 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 620 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 621 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 622 HL BITS 1 DEN 26D4 GRT NA S NA
#> 623 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 624 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 625 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 626 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 627 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 628 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 629 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 630 HL BITS 4 POL 67BC TVL 75 S NA
#> 631 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 632 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 633 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 634 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 635 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 636 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 637 HL BITS 1 DEN 26D4 TVL NA R TRUE
#> 638 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 639 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 640 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 641 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 642 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 643 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 644 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 645 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 646 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 647 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 648 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 649 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 650 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 651 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 652 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 653 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 654 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 655 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 656 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 657 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 658 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 659 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 660 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 661 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 662 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 663 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 664 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 665 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 666 HL BITS 1 DEN 26D4 GRT NA S NA
#> 667 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 668 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 669 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 670 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 671 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 672 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 673 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 674 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 675 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 676 HL BITS 1 SWE 77AR TVL 95 <NA> NA
#> 677 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 678 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 679 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 680 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 681 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 682 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 683 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 684 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 685 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 686 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 687 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 688 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 689 HL BITS 1 DEN 26D4 GRT NA S NA
#> 690 HL BITS 1 DEN 26D4 GRT NA S NA
#> 691 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 692 HL BITS 1 DEN 26D4 GRT NA S NA
#> 693 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 694 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 695 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 696 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 697 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 698 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 699 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 700 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 701 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 702 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 703 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 704 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 705 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 706 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 707 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 708 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 709 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 710 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 711 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 712 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 713 HL BITS 4 POL 67BC TVL 75 S NA
#> 714 HL BITS 1 DEN 26D4 GRT NA S NA
#> 715 HL BITS 1 DEN 26D4 GRT NA S NA
#> 716 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 717 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 718 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 719 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 720 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 721 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 722 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 723 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 724 HL BITS 1 DEN 26D4 TVL NA R TRUE
#> 725 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 726 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 727 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 728 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 729 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 730 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 731 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 732 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 733 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 734 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 735 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 736 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 737 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 738 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 739 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 740 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 741 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 742 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 743 HL BITS 1 DEN 26D4 GRT NA S NA
#> 744 HL BITS 1 DEN 26D4 GRT NA S NA
#> 745 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 746 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 747 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 748 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 749 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 750 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 751 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 752 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 753 HL BITS 4 SWE 77AR FOT 100 <NA> NA
#> 754 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 755 HL BITS 1 LAT LAIZ LBT NA <NA> NA
#> 756 HL BITS 1 LAT LAIZ LBT NA <NA> NA
#> 757 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 758 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 759 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 760 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 761 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 762 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 763 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 764 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 765 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 766 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 767 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 768 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 769 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 770 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 771 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 772 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 773 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 774 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 775 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 776 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 777 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 778 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 779 HL BITS 1 DEN 26D4 TVL NA R NA
#> 780 HL BITS 4 DEN 26D4 TVL NA R NA
#> 781 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 782 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 783 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 784 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 785 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 786 HL BITS 4 POL 67BC TVL 75 S NA
#> 787 HL BITS 4 SWE 77AR TVL 95 S TRUE
#> 788 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 789 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 790 HL BITS 1 DEN 26D4 GRT NA S NA
#> 791 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 792 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 793 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 794 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 795 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 796 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 797 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 798 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 799 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 800 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 801 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 802 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 803 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 804 HL BITS 1 LAT AA36 LBT NA <NA> NA
#> 805 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 806 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 807 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 808 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 809 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 810 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 811 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 812 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 813 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 814 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 815 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 816 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 817 HL BITS 4 DEN 26D4 TVL NA R NA
#> 818 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 819 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 820 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 821 HL BITS 1 DEN 26D4 TVL NA R NA
#> 822 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 823 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 824 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 825 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 826 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 827 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 828 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 829 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 830 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 831 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 832 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 833 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 834 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 835 HL BITS 1 LAT 67BC TVL 75 R TRUE
#> 836 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 837 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 838 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 839 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 840 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 841 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 842 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 843 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 844 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 845 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 846 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 847 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 848 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 849 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 850 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 851 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 852 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 853 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 854 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 855 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 856 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 857 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 858 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 859 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 860 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 861 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 862 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 863 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 864 HL BITS 1 DEN 26D4 GRT NA S NA
#> 865 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 866 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 867 HL BITS 1 DEN 26D4 GRT NA S NA
#> 868 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 869 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 870 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 871 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 872 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 873 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 874 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 875 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 876 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 877 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 878 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 879 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 880 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 881 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 882 HL BITS 4 RUS RUNT TVL NA <NA> NA
#> 883 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 884 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 885 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 886 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 887 HL BITS 1 DEN 26D4 GRT NA S NA
#> 888 HL BITS 1 DEN 26D4 GRT NA S NA
#> 889 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 890 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 891 HL BITS 1 DEN 26D4 GRT NA S NA
#> 892 HL BITS 1 DEN 26D4 GRT NA S NA
#> 893 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 894 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 895 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 896 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 897 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 898 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 899 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 900 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 901 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 902 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 903 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 904 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 905 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 906 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 907 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 908 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 909 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 910 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 911 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 912 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 913 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 914 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 915 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 916 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 917 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 918 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 919 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 920 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 921 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 922 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 923 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 924 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 925 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 926 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 927 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 928 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 929 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 930 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 931 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 932 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 933 HL BITS 4 SWE 77AR TVL 75 S NA
#> 934 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 935 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 936 HL BITS 1 DEN 26D4 GRT NA S NA
#> 937 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 938 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 939 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 940 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 941 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 942 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 943 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 944 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 945 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 946 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 947 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 948 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 949 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 950 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 951 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 952 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 953 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 954 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 955 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 956 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 957 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 958 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 959 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 960 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 961 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 962 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 963 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 964 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 965 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 966 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 967 HL BITS 1 SWE 77AR TVL 95 <NA> NA
#> 968 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 969 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 970 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 971 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 972 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 973 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 974 HL BITS 4 LTU LTDA TVS NA <NA> NA
#> 975 HL BITS 4 POL 67BC TVL 75 S NA
#> 976 HL BITS 4 POL 67BC TVL 75 S NA
#> 977 HL BITS 4 POL 67BC TVL 75 S NA
#> 978 HL BITS 4 POL 67BC TVL 75 S NA
#> 979 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 980 HL BITS 4 LTU LTDA TVS NA <NA> NA
#> 981 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 982 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 983 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 984 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 985 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 986 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 987 HL BITS 4 DEN 26D4 TVL NA R NA
#> 988 HL BITS 4 DEN 26D4 TVL NA R NA
#> 989 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 990 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 991 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 992 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 993 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 994 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 995 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 996 HL BITS 4 DEN 26D4 TVL NA R TRUE
#> 997 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 998 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 999 HL BITS 1 LAT AA36 LBT NA <NA> NA
#> 1000 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 1001 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1002 HL BITS 1 SWE 77AR TVL 60 <NA> NA
#> 1003 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1004 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1005 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1006 HL BITS 1 DEN 26D4 TVL NA R NA
#> 1007 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 1008 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1009 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1010 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1011 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1012 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1013 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1014 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1015 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1016 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1017 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1018 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1019 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1020 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1021 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1022 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1023 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1024 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1025 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1026 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1027 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1028 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1029 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1030 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1031 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1032 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1033 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1034 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1035 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 1036 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1037 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1038 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1039 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1040 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1041 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1042 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1043 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1044 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1045 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1046 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1047 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1048 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1049 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1050 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1051 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1052 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1053 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1054 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1055 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1056 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1057 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1058 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1059 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1060 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1061 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1062 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1063 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1064 HL BITS 4 POL 67BC TVL 75 S NA
#> 1065 HL BITS 4 SWE 77AR TVL 95 S TRUE
#> 1066 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1067 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1068 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1069 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1070 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1071 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1072 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1073 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1074 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1075 HL BITS 1 LTU LTDA TVS NA <NA> NA
#> 1076 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1077 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1078 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1079 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1080 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1081 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1082 HL BITS 4 DEN 26D4 TVL NA R TRUE
#> 1083 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1084 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1085 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1086 HL BITS 4 SWE 77AR FOT 180 <NA> NA
#> 1087 HL BITS 1 DEN 26D4 TVL NA R NA
#> 1088 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1089 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 1090 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1091 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1092 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1093 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1094 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1095 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1096 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1097 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1098 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1099 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1100 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1101 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1102 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1103 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1104 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1105 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1106 HL BITS 1 LAT AA36 LBT NA <NA> NA
#> 1107 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1108 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1109 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1110 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1111 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1112 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1113 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1114 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 1115 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1116 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1117 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1118 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1119 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1120 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1121 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1122 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1123 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1124 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1125 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1126 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1127 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1128 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1129 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1130 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1131 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1132 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1133 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1134 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1135 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1136 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1137 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1138 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1139 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1140 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1141 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1142 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1143 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1144 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1145 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1146 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1147 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1148 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1149 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1150 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1151 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1152 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1153 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1154 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1155 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1156 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1157 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1158 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1159 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1160 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1161 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1162 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1163 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1164 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1165 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1166 HL BITS 1 SWE 77AR TVL 95 <NA> NA
#> 1167 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1168 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1169 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1170 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1171 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1172 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1173 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1174 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1175 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1176 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1177 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1178 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1179 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1180 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1181 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1182 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1183 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1184 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 1185 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1186 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1187 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1188 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1189 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1190 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1191 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 1192 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1193 HL BITS 4 DEN 26D4 TVL NA R TRUE
#> 1194 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1195 HL BITS 4 RUS RUNT TVL NA <NA> NA
#> 1196 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1197 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1198 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1199 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1200 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1201 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1202 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1203 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1204 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1205 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1206 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1207 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1208 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1209 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1210 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1211 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1212 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1213 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1214 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1215 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1216 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1217 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1218 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 1219 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1220 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1221 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1222 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1223 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1224 HL BITS 4 SWE 77AR TVL 75 S NA
#> 1225 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1226 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1227 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1228 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1229 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1230 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1231 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1232 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1233 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1234 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1235 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1236 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1237 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1238 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1239 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1240 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1241 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1242 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1243 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1244 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1245 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1246 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1247 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1248 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1249 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1250 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1251 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1252 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1253 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1254 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1255 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1256 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1257 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1258 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 1259 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1260 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1261 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1262 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1263 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1264 HL BITS 1 LAT 67BC TVL 75 R TRUE
#> 1265 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1266 HL BITS 4 POL 67BC TVL 75 S NA
#> 1267 HL BITS 4 POL 67BC TVL 75 S NA
#> 1268 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1269 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1270 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1271 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1272 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1273 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1274 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1275 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1276 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1277 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1278 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1279 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1280 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1281 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1282 HL BITS 4 SWE 77AR TVL 75 S TRUE
#> 1283 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1284 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1285 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1286 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1287 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1288 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1289 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1290 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1291 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1292 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1293 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1294 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1295 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 1296 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1297 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1298 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1299 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1300 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1301 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1302 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1303 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1304 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1305 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1306 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1307 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1308 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1309 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1310 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1311 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1312 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1313 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1314 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1315 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 1316 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1317 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1318 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1319 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1320 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1321 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1322 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1323 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1324 HL BITS 4 RUS RUNT TVL NA <NA> NA
#> 1325 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1326 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1327 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1328 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1329 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1330 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1331 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1332 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1333 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1334 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1335 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1336 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1337 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1338 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1339 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1340 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1341 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1342 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1343 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1344 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1345 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1346 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1347 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1348 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1349 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1350 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1351 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1352 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1353 HL BITS 1 LAT AA36 LBT NA <NA> NA
#> 1354 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1355 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1356 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1357 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1358 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1359 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1360 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1361 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1362 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1363 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1364 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1365 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1366 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1367 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1368 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1369 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1370 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1371 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1372 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1373 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1374 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1375 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1376 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1377 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1378 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1379 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1380 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1381 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1382 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1383 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1384 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1385 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1386 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1387 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1388 HL BITS 4 LTU LTDA TVS NA <NA> NA
#> 1389 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1390 HL BITS 4 POL 67BC TVL 75 S NA
#> 1391 HL BITS 4 POL 67BC TVL 75 S NA
#> 1392 HL BITS 4 POL 67BC TVL 75 S NA
#> 1393 HL BITS 4 SWE 77AR TVL 95 S TRUE
#> 1394 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1395 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1396 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1397 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1398 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1399 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1400 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1401 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1402 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1403 HL BITS 4 SWE 77AR TVL 75 S TRUE
#> 1404 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1405 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1406 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1407 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1408 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1409 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1410 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1411 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1412 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1413 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1414 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1415 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1416 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1417 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1418 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1419 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1420 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1421 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1422 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1423 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1424 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1425 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1426 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1427 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1428 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1429 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1430 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1431 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1432 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1433 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 1434 HL BITS 4 SWE 77AR FOT 100 <NA> NA
#> 1435 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1436 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1437 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1438 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1439 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1440 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1441 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1442 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1443 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1444 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1445 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1446 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1447 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1448 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1449 HL BITS 4 DEN 26D4 TVL NA R TRUE
#> 1450 HL BITS 4 RUS RUNT TVL NA <NA> NA
#> 1451 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1452 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1453 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1454 HL BITS 4 SWE 77AR TVL 95 <NA> NA
#> 1455 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1456 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1457 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1458 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1459 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1460 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1461 HL BITS 1 SWE 77AR FOT 0 <NA> NA
#> 1462 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1463 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1464 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1465 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1466 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1467 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1468 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1469 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1470 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1471 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1472 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1473 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1474 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1475 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1476 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1477 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1478 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1479 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1480 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1481 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1482 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1483 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1484 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1485 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1486 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1487 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1488 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1489 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1490 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1491 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1492 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1493 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1494 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1495 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1496 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1497 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1498 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1499 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1500 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1501 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1502 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1503 HL BITS 1 SWE 77AR TVL 75 S NA
#> 1504 HL BITS 4 POL 67BC TVL 75 S NA
#> 1505 HL BITS 4 POL 67BC TVL 75 S NA
#> 1506 HL BITS 4 POL 67BC TVL 75 S NA
#> 1507 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1508 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1509 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1510 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1511 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1512 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1513 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1514 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1515 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1516 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1517 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 1518 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1519 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1520 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1521 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1522 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1523 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1524 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1525 HL BITS 1 LAT 67BC TVL 75 R TRUE
#> 1526 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1527 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1528 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1529 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1530 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1531 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1532 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1533 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1534 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1535 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1536 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1537 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1538 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1539 HL BITS 4 SWE 77AR TVL 95 <NA> NA
#> 1540 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1541 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1542 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1543 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1544 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1545 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1546 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1547 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1548 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1549 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1550 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1551 HL BITS 4 SWE 77AR FOT 100 <NA> NA
#> 1552 HL BITS 4 SWE 77AR GOV 100 <NA> NA
#> 1553 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1554 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1555 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1556 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1557 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1558 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1559 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1560 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1561 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1562 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1563 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1564 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1565 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1566 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1567 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1568 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1569 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1570 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1571 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1572 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1573 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1574 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1575 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1576 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1577 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1578 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1579 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1580 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1581 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1582 HL BITS 1 DEN 26D4 TVL NA R TRUE
#> 1583 HL BITS 1 LAT AA36 TVS NA <NA> NA
#> 1584 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1585 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 1586 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1587 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1588 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1589 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1590 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1591 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1592 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1593 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1594 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1595 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1596 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1597 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1598 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1599 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1600 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1601 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1602 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1603 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1604 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1605 HL BITS 4 SWE 77AR TVL 75 S NA
#> 1606 HL BITS 4 POL 67BC TVL 75 S TRUE
#> 1607 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1608 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1609 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1610 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1611 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1612 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1613 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1614 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1615 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1616 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1617 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1618 HL BITS 1 SWE 77AR TVL 60 <NA> NA
#> 1619 HL BITS 1 SWE 77AR TVL 60 <NA> NA
#> 1620 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1621 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1622 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1623 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 1624 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1625 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1626 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1627 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1628 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1629 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1630 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1631 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1632 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1633 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1634 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1635 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1636 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1637 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1638 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1639 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1640 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1641 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1642 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1643 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1644 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1645 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1646 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1647 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1648 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1649 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1650 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1651 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1652 HL BITS 1 SWE 77AR TVL 75 S NA
#> 1653 HL BITS 1 SWE 77AR TVL 75 S NA
#> 1654 HL BITS 4 POL 67BC TVL 75 S NA
#> 1655 HL BITS 4 LAT 67BC TVL 75 R TRUE
#> 1656 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1657 HL BITS 1 RUS RUJB TVL NA <NA> NA
#> 1658 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1659 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1660 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1661 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1662 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1663 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1664 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1665 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1666 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1667 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1668 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1669 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1670 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1671 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1672 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1673 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1674 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1675 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1676 HL BITS 4 SWE 77AR TVL 95 <NA> NA
#> 1677 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1678 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1679 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1680 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1681 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1682 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1683 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1684 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 1685 HL BITS 4 SWE 77AR GOV 75 <NA> NA
#> 1686 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1687 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1688 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1689 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1690 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1691 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1692 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1693 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1694 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1695 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1696 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1697 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1698 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1699 HL BITS 4 DEN 26D4 TVL NA <NA> NA
#> 1700 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1701 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1702 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1703 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1704 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1705 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1706 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1707 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1708 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1709 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1710 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1711 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1712 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1713 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1714 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1715 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1716 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1717 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1718 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1719 HL BITS 4 GFR 06S1 H20 NA <NA> NA
#> 1720 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1721 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1722 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1723 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1724 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1725 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1726 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1727 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1728 HL BITS 1 SWE 77AR FOT 135 <NA> NA
#> 1729 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1730 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1731 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1732 HL BITS 1 DEN 26D4 TVL 75 S NA
#> 1733 HL BITS 1 DEN 26D4 TVL NA S NA
#> 1734 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1735 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1736 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1737 HL BITS 1 SWE 77AR TVL 75 S TRUE
#> 1738 HL BITS 4 GFR 06S1 TVS NA <NA> NA
#> 1739 HL BITS 4 SWE 77AR TVL 75 <NA> NA
#> 1740 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1741 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1742 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1743 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1744 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1745 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1746 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1747 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1748 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1749 HL BITS 4 LAT AA36 TVS 75 <NA> NA
#> 1750 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1751 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1752 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1753 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1754 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1755 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1756 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1757 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1758 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1759 HL BITS 1 SWE 77AR TVL 95 S TRUE
#> 1760 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1761 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1762 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1763 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1764 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1765 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1766 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1767 HL BITS 1 SWE 77AR FOT 185 <NA> NA
#> 1768 HL BITS 4 SWE 77AR FOT 180 <NA> NA
#> 1769 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1770 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1771 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1772 HL BITS 1 RUS RUJB HAK NA <NA> NA
#> 1773 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1774 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1775 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1776 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1777 HL BITS 1 SWE 77AR FOT 225 <NA> NA
#> 1778 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1779 HL BITS 1 GFR 06S1 TVS NA <NA> NA
#> 1780 HL BITS 1 SWE 77AR TVL 75 <NA> NA
#> 1781 HL BITS 1 RUS RUS6 TVL NA <NA> NA
#> 1782 HL BITS 4 GFR 06S1 TVS NA <NA> NA
#> 1783 HL BITS 4 DEN 26D4 TVL NA R NA
#> 1784 HL BITS 4 GFR 06S1 TVS NA <NA> NA
#> 1785 HL BITS 4 DEN 26D4 TVL 75 S NA
#> 1786 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1787 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1788 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1789 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1790 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1791 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1792 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1793 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1794 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1795 HL BITS 1 DEN 26D4 GRT 60 <NA> NA
#> 1796 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1797 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1798 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1799 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1800 HL BITS 1 SWE 77AR FOT 180 <NA> NA
#> 1801 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1802 HL BITS 4 SWE 77AR FOT 185 <NA> NA
#> 1803 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1804 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1805 HL BITS 1 GFR 06SL TVS NA <NA> NA
#> 1806 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1807 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1808 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1809 HL BITS 1 SWE 77AR TVL 75 S NA
#> 1810 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1811 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1812 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1813 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1814 HL BITS 4 SWE 77AR TVL 95 S TRUE
#> 1815 HL BITS 4 LAT 67BC TVL 75 R TRUE
#> 1816 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1817 HL BITS 4 RUS RUJB TVL NA <NA> NA
#> 1818 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1819 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1820 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1821 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1822 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1823 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1824 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1825 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1826 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1827 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1828 HL BITS 1 DEN 26D4 GRT 110 <NA> NA
#> 1829 HL BITS 1 SWE 77AR GOV 50 <NA> NA
#> 1830 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1831 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1832 HL BITS 1 POL 67BC TVL NA <NA> NA
#> 1833 HL BITS 4 DEN 26D4 TVL NA R TRUE
#> 1834 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1835 HL BITS 4 POL 67BC TVL NA <NA> NA
#> 1836 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1837 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1838 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1839 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1840 HL BITS 4 SWE 77AR TVL 95 <NA> NA
#> 1841 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1842 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1843 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1844 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1845 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1846 HL BITS 1 RUS RUNT TVL NA <NA> NA
#> 1847 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1848 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1849 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1850 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1851 HL BITS 1 SWE 77AR GOV 100 <NA> NA
#> 1852 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1853 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1854 HL BITS 1 POL 67BC TVL 75 S TRUE
#> 1855 HL BITS 1 DEN 26D4 TVL NA S TRUE
#> 1856 HL BITS 4 GFR 06SL TVS NA <NA> NA
#> 1857 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1858 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1859 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1860 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1861 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1862 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1863 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1864 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1865 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1866 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1867 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1868 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1869 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1870 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1871 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1872 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1873 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1874 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1875 HL BITS 1 GFR 06S1 CHP NA <NA> NA
#> 1876 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1877 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1878 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1879 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1880 HL BITS 1 POL AA36 P20 NA <NA> NA
#> 1881 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1882 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1883 HL BITS 1 LAT 90MX LBT NA <NA> NA
#> 1884 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1885 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1886 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1887 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1888 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1889 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1890 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1891 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1892 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1893 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1894 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1895 HL BITS 1 SWE 77AR FOT 203 <NA> NA
#> 1896 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1897 HL BITS 4 DEN 26D4 TVL NA S TRUE
#> 1898 HL BITS 1 DEN 26D4 GRT NA <NA> NA
#> 1899 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1900 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1901 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1902 HL BITS 1 LAT RUEK DT NA <NA> NA
#> 1903 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1904 HL BITS 1 SWE 77AR GOV 90 <NA> NA
#> 1905 HL BITS 1 RUS RUEK DT NA <NA> NA
#> 1906 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1907 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1908 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1909 HL BITS 4 SWE 77AR FOT 203 <NA> NA
#> 1910 HL BITS 1 DEN 26D4 GRT NA S NA
#> 1911 HL BITS 1 GFR 06S1 H20 NA <NA> NA
#> 1912 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1913 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1914 HL BITS 1 POL 67BC P20 NA <NA> NA
#> 1915 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1916 HL BITS 1 RUS RUNT HAK NA <NA> NA
#> 1917 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1918 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1919 HL BITS 1 SWE 77AR FOT 235 <NA> NA
#> 1920 HL BITS 4 LAT AA36 LBT NA <NA> NA
#> 1921 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1922 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> 1923 HL BITS 4 SWE 77AR FOT 225 <NA> NA
#> StNo HaulNo Year SpecCodeType SpecCode SpecVal Sex TotalNo
#> 1 83 40 1998 T 164712 1 <NA> 17.00
#> 2 83 40 1998 T 164712 1 <NA> 17.00
#> 3 83 40 1998 T 164712 1 <NA> 17.00
#> 4 83 40 1998 T 164712 1 <NA> 17.00
#> 5 83 40 1998 T 164712 1 <NA> 17.00
#> 6 83 40 1998 T 164712 1 <NA> 17.00
#> 7 83 40 1998 T 164712 1 <NA> 17.00
#> 8 83 40 1998 T 164712 1 <NA> 17.00
#> 9 83 40 1998 T 164712 1 <NA> 17.00
#> 10 83 40 1998 T 164712 1 <NA> 17.00
#> 11 83 40 1998 T 164712 1 <NA> 17.00
#> 12 45 25 1996 W 126436 1 <NA> 93.00
#> 13 80 32 1993 W 126436 1 <NA> 454.00
#> 14 83 40 1998 T 164712 1 <NA> 17.00
#> 15 43 22 1994 T 164712 1 <NA> 37.00
#> 16 9 5 1996 W 126436 1 <NA> 406.00
#> 17 191 3 1998 T 164712 1 <NA> 546.00
#> 18 46 20 1993 W 126436 1 <NA> 326.00
#> 19 71 36 2003 T 164712 1 <NA> 255.00
#> 20 000001 19 1991 W 126436 1 <NA> 282.00
#> 21 117 50 1994 T 164712 1 <NA> 775.00
#> 22 75 40 1996 W 126436 1 <NA> 29.00
#> 23 584 18 2000 W 126436 1 <NA> 454.00
#> 24 10 4 2002 T 164712 1 <NA> 1958.00
#> 25 136 64 1998 T 164712 1 <NA> 130.00
#> 26 26073 50 1991 W 126436 1 <NA> 77.00
#> 27 573 11 2002 W 126436 1 <NA> 3090.00
#> 28 220 21 2000 W 126436 1 <NA> 1076.00
#> 29 237 34 2000 W 126436 1 <NA> 638.00
#> 30 106 57 1991 W 126436 1 <NA> 51.00
#> 31 111 47 1996 W 126436 1 <NA> 78.00
#> 32 231 26 1996 W 126436 1 <NA> 54.00
#> 33 247 2 1995 W 126436 1 <NA> 2736.00
#> 34 652 17 1999 T 164712 1 <NA> 1484.00
#> 35 207 15 1998 T 164712 1 <NA> 20.00
#> 36 162 72 1993 W 126436 1 <NA> 128.00
#> 37 53 30 1996 W 126436 1 <NA> 197.00
#> 38 <NA> 13 2006 W 126436 1 <NA> 24.00
#> 39 57 23 1995 W 126436 1 <NA> 223.00
#> 40 24316 41 2008 T 164712 1 <NA> 864.00
#> 41 26021 29 1992 W 126436 1 <NA> 68.00
#> 42 26073 50 1991 W 126436 1 <NA> 77.00
#> 43 74 39 1994 T 164712 1 <NA> 457.00
#> 44 222 26 1998 T 164712 1 <NA> 126.00
#> 45 44 24 1994 T 164712 1 <NA> 260.00
#> 46 95 66 2005 W 126436 1 <NA> 764.00
#> 47 58 10 1993 W 126436 1 <NA> 85.00
#> 48 6 3 2001 T 164712 1 <NA> 132.00
#> 49 000001 12 1991 W 126436 1 <NA> 49.00
#> 50 17 9 1993 W 126436 1 <NA> 281.00
#> 51 000001 6 1993 W 126436 1 <NA> 22.00
#> 52 252 21 1993 W 126436 1 <NA> 5932.00
#> 53 26132 24 2008 T 164712 1 <NA> 1696.00
#> 54 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 55 <NA> 33 1998 T 164712 1 <NA> 302.00
#> 56 19 17 2009 W 126436 1 <NA> 972.00
#> 57 81 44 1991 W 126436 1 <NA> 164.00
#> 58 94 46 2000 T 164712 1 <NA> 180.00
#> 59 <NA> 13 1996 W 126436 1 <NA> 194.00
#> 60 33 14 1995 W 126436 1 <NA> 32.00
#> 61 100 1 2010 W 126436 1 <NA> 552.00
#> 62 16 8 2000 W 126436 1 <NA> 85.00
#> 63 66 36 1996 W 126436 1 <NA> 43.00
#> 64 74 23 1996 W 126436 1 <NA> 936.00
#> 65 1 1 2004 W 126436 1 <NA> 470.00
#> 66 85 37 1993 W 126436 1 <NA> 1332.00
#> 67 199 8 1998 T 164712 1 <NA> 1016.00
#> 68 123 46 1995 W 126436 1 <NA> 231.00
#> 69 60 17 2010 T 164712 1 <NA> 566.00
#> 70 267 52 2009 W 126436 1 U 650.00
#> 71 26021 29 1992 W 126436 1 <NA> 68.00
#> 72 25 72 1994 T 164712 1 <NA> 428.00
#> 73 287 32 1994 W 126436 1 <NA> 2924.00
#> 74 594 27 2000 W 126436 1 <NA> 842.00
#> 75 2 2 2004 W 126436 1 <NA> 286.00
#> 76 <NA> 37 1998 T 164712 1 <NA> 668.00
#> 77 11 3 1995 W 126436 1 <NA> 80.00
#> 78 73 34 1994 T 164712 1 <NA> 764.00
#> 79 51 29 1996 W 126436 1 <NA> 212.00
#> 80 95 44 1996 W 126436 1 <NA> 248.00
#> 81 26211 3 2011 W 126436 1 U 1130.00
#> 82 18 7 1997 T 164712 1 <NA> 75.00
#> 83 756 26 1997 W 126436 1 <NA> 22.00
#> 84 000001 11 1991 W 126436 1 <NA> 82.00
#> 85 60 23 2010 T 164712 1 <NA> 6475.00
#> 86 130 61 1998 T 164712 1 <NA> 493.00
#> 87 <NA> 19 1995 W 126436 1 <NA> 466.00
#> 88 63 32 1994 T 164712 1 <NA> 40.00
#> 89 Mar 18 1994 T 164712 1 <NA> 48.00
#> 90 46 26 1996 W 126436 1 <NA> 110.00
#> 91 <NA> 5 1999 T 164712 1 <NA> 94.00
#> 92 48 22 1993 W 126436 1 <NA> 586.00
#> 93 902 34 2001 T 164712 1 <NA> 278.00
#> 94 179 16 2009 W 126436 1 <NA> 943.00
#> 95 7 32 2006 W 126436 1 <NA> 234.00
#> 96 <NA> 60 2003 T 164712 1 <NA> 194.00
#> 97 79 55 1992 W 126436 1 <NA> 4.00
#> 98 56 40 2011 T 164712 1 <NA> 4360.00
#> 99 39 42 2011 W 126436 1 <NA> 710.00
#> 100 47 51 1996 W 126436 1 <NA> 640.00
#> 101 227 22 1996 W 126436 1 <NA> 408.00
#> 102 25 68 1996 T 164712 1 <NA> 104.00
#> 103 81 44 1991 W 126436 1 <NA> 164.00
#> 104 26073 50 1991 W 126436 1 <NA> 77.00
#> 105 02Feb 10 1999 T 164712 1 <NA> 218.00
#> 106 2 9 1999 T 164712 1 <NA> 1022.00
#> 107 206 14 1998 T 164712 1 <NA> 194.00
#> 108 75 23 1995 W 126436 1 <NA> 496.00
#> 109 223 30 2006 W 126436 1 U 621.00
#> 110 <NA> 10 2001 T 164712 1 <NA> 116.00
#> 111 26014 21 2008 T 164712 1 <NA> 962.00
#> 112 26132 24 2008 T 164712 1 <NA> 1696.00
#> 113 51 26 2008 T 164712 1 <NA> 562.00
#> 114 118 51 1994 T 164712 1 <NA> 198.00
#> 115 2810 36 1992 W 126436 1 <NA> 15.00
#> 116 56 7 1992 W 126436 1 <NA> 188.00
#> 117 584 18 2000 W 126436 1 <NA> 454.00
#> 118 36 20 1996 W 126436 1 <NA> 103.00
#> 119 66 69 1998 T 164712 1 <NA> 58.00
#> 120 249 45 1998 T 164712 1 <NA> 356.00
#> 121 100019 12 1999 T 164712 1 <NA> 108.00
#> 122 03Mar 2 1991 W 126436 1 <NA> 108.00
#> 123 179 15 2009 W 126436 1 <NA> 539.00
#> 124 25027 7 2006 T 164712 1 <NA> 158.00
#> 125 52 26 1994 T 164712 1 <NA> 2.00
#> 126 26021 29 1992 W 126436 1 <NA> 68.00
#> 127 56 7 1992 W 126436 1 <NA> 188.00
#> 128 <NA> 12 2000 W 126436 1 <NA> 1661.00
#> 129 75 38 2000 T 164712 1 <NA> 45.00
#> 130 902 34 2004 T 164712 1 <NA> 1156.00
#> 131 30 16 1996 W 126436 1 <NA> 1965.00
#> 132 98 48 2010 W 126436 1 <NA> 646.00
#> 133 213 24 2010 W 126436 1 <NA> 2531.00
#> 134 65 119 1999 T 164712 1 <NA> 884.00
#> 135 03Mar 54 1999 T 164712 1 <NA> 778.00
#> 136 2605 45 1991 W 126436 1 <NA> 196.00
#> 137 25225 78 1991 W 126436 1 <NA> 179.00
#> 138 56 27 2001 T 164712 1 <NA> 100.00
#> 139 02Feb 28 1993 W 126436 1 <NA> 40.00
#> 140 134 49 1995 W 126436 1 <NA> 180.00
#> 141 254 9 1995 W 126436 1 <NA> 274.00
#> 142 77 39 2003 T 164712 1 <NA> 277.00
#> 143 <NA> 6 2004 T 164712 1 <NA> 2396.00
#> 144 <NA> 18 2000 W 126436 1 <NA> 1056.00
#> 145 270 47 2000 W 126436 1 <NA> 272.00
#> 146 89 45 2000 T 164712 1 <NA> 384.00
#> 147 2504 46 1992 W 126436 1 <NA> 58.00
#> 148 166 16 2010 W 126436 1 <NA> 558.00
#> 149 62 34 1996 W 126436 1 <NA> 36.00
#> 150 <NA> 7 1996 W 126436 1 <NA> 26.00
#> 151 11 4 1997 T 164712 1 <NA> 8.00
#> 152 746 17 1997 W 126436 1 <NA> 468.00
#> 153 745 16 1997 W 126436 1 <NA> 47.65
#> 154 <NA> 34 1998 T 164712 1 <NA> 290.00
#> 155 03Mar 63 1998 T 164712 1 <NA> 464.00
#> 156 <NA> 37 1998 T 164712 1 <NA> 668.00
#> 157 738 35 1998 T 164712 1 <NA> 8.00
#> 158 715 17 1998 T 164712 1 <NA> 758.00
#> 159 266 37 2009 W 126436 1 <NA> 673.00
#> 160 44 69 1999 T 164712 1 <NA> 152.00
#> 161 03Mar 69 1999 T 164712 1 <NA> 274.00
#> 162 72 1 1991 W 126436 1 <NA> 142.00
#> 163 01Jan 24 1991 W 126436 1 <NA> 34.00
#> 164 <NA> 44 1995 W 126436 1 <NA> 30.00
#> 165 94 42 1995 W 126436 1 <NA> 48.00
#> 166 2024 27 2003 T 164712 1 <NA> 371.00
#> 167 44 24 1994 T 164712 1 <NA> 260.00
#> 168 283 28 1994 W 126436 1 <NA> 268.00
#> 169 17 32 2004 T 164712 1 <NA> 345.00
#> 170 64 31 2000 W 126436 1 <NA> 24.00
#> 171 87 44 2000 T 164712 1 <NA> 150.00
#> 172 213 24 2010 W 126436 1 <NA> 2531.00
#> 173 24237 31 2010 W 126436 1 <NA> 1098.00
#> 174 9 6 1992 W 126436 1 <NA> 5.00
#> 175 90 39 1996 W 126436 1 <NA> 50.00
#> 176 754 24 1997 W 126436 1 <NA> 418.00
#> 177 2 8 1999 T 164712 1 <NA> 1194.00
#> 178 21 8 1995 W 126436 1 <NA> 27.00
#> 179 95 43 1995 W 126436 1 <NA> 20.00
#> 180 <NA> 4 1995 W 126436 1 <NA> 26.00
#> 181 250 5 1995 W 126436 1 <NA> 102.00
#> 182 36 24 1991 W 126436 1 <NA> 41.00
#> 183 26071 48 1991 W 126436 1 <NA> 213.00
#> 184 28 24 1993 W 126436 1 <NA> 3218.00
#> 185 60 12 1993 W 126436 1 <NA> 378.00
#> 186 133 55 2002 T 164712 1 <NA> 107.00
#> 187 85 39 2002 T 164712 1 <NA> 420.00
#> 188 78 27 1994 W 126436 1 <NA> 350.00
#> 189 670 2 2010 W 126436 1 U 2505.05
#> 190 26 13 2000 W 126436 1 <NA> 42.00
#> 191 220 21 2000 W 126436 1 <NA> 1076.00
#> 192 32 18 1996 W 126436 1 <NA> 1610.00
#> 193 50 28 1996 W 126436 1 <NA> 225.00
#> 194 2517 17 1992 W 126436 1 <NA> 129.00
#> 195 26021 29 1992 W 126436 1 <NA> 68.00
#> 196 28 38 1992 T 164712 1 <NA> 68.00
#> 197 11 4 1997 T 164712 1 <NA> 8.00
#> 198 185 9 1997 W 126436 1 <NA> 1116.00
#> 199 746 17 1997 W 126436 1 <NA> 468.00
#> 200 24001 16 2005 T 164712 1 <NA> 248.00
#> 201 108 10 2005 W 126436 1 <NA> 178.00
#> 202 22 10 2005 W 126436 1 <NA> 717.00
#> 203 130 61 1998 T 164712 1 <NA> 493.00
#> 204 03Mar 55 1998 T 164712 1 <NA> 226.00
#> 205 230 31 1998 T 164712 1 <NA> 6.00
#> 206 718 20 1998 T 164712 1 <NA> 790.00
#> 207 720 22 1998 T 164712 1 <NA> 208.00
#> 208 44 20 1999 T 164712 1 <NA> 54.00
#> 209 02Feb 14 1999 T 164712 1 <NA> 98.00
#> 210 000001 23 1995 W 126436 1 <NA> 155.00
#> 211 157 59 1995 W 126436 1 <NA> 29.00
#> 212 81 44 1991 W 126436 1 <NA> 164.00
#> 213 2406 29 1991 W 126436 1 <NA> 41.00
#> 214 26071 48 1991 W 126436 1 <NA> 213.00
#> 215 49 24 2003 T 164712 1 <NA> 89.00
#> 216 39 42 2011 W 126436 1 <NA> 710.00
#> 217 43 33 2002 T 164712 1 <NA> 162.00
#> 218 68 34 1994 T 164712 1 <NA> 752.00
#> 219 100 1 2010 W 126436 1 <NA> 552.00
#> 220 102 2 2010 W 126436 1 <NA> 727.00
#> 221 124 5 2010 W 126436 1 <NA> 520.00
#> 222 213 24 2010 W 126436 1 <NA> 2531.00
#> 223 45 39 2010 W 126436 1 <NA> 945.00
#> 224 31 31 2004 W 126436 1 <NA> 464.00
#> 225 <NA> 68 2004 T 164712 1 <NA> 28.00
#> 226 1 8 2000 W 126436 1 <NA> 500.00
#> 227 251 45 2000 W 126436 1 <NA> 102.00
#> 228 78 27 1996 W 126436 1 <NA> 402.00
#> 229 26132 1 2007 T 164712 1 <NA> 732.00
#> 230 70 46 2009 W 126436 1 <NA> 545.00
#> 231 108 10 2005 W 126436 1 <NA> 178.00
#> 232 163 12 2008 W 126436 1 <NA> 370.00
#> 233 51 23 2008 T 164712 1 <NA> 3344.00
#> 234 01Jan 46 1998 T 164712 1 <NA> 1096.00
#> 235 69 32 1999 T 164712 1 <NA> 1.00
#> 236 96 44 1999 T 164712 1 <NA> 108.00
#> 237 100030 18 1999 T 164712 1 <NA> 460.00
#> 238 52 9 2011 W 126436 1 U 1520.00
#> 239 56 40 2011 T 164712 1 <NA> 4360.00
#> 240 173 15 2011 W 126436 1 <NA> 297.00
#> 241 32 31 1995 W 126436 1 <NA> 3112.00
#> 242 66 83 1995 W 126436 1 <NA> 24.00
#> 243 91 47 2003 T 164712 1 <NA> 448.00
#> 244 24100 50 2003 T 164712 1 <NA> 245.00
#> 245 8 4 2002 T 164712 1 <NA> 482.00
#> 246 85 37 1993 W 126436 1 <NA> 1332.00
#> 247 79 31 1993 W 126436 1 <NA> 378.00
#> 248 82 31 1994 W 126436 1 <NA> 2875.24
#> 249 33 53 1994 T 164712 1 <NA> 2608.00
#> 250 2503 32 1991 W 126436 1 <NA> 138.00
#> 251 30 15 2000 W 126436 1 <NA> 114.00
#> 252 82 98 2000 W 126436 1 <NA> 120.00
#> 253 80 41 2000 T 164712 1 <NA> 466.00
#> 254 24047 43 2007 T 164712 1 <NA> 129.00
#> 255 132 57 1996 W 126436 1 <NA> 215.00
#> 256 <NA> 17 1996 W 126436 1 <NA> 405.00
#> 257 76 25 1996 W 126436 1 <NA> 546.00
#> 258 204 25 1997 W 126436 1 <NA> 24.00
#> 259 2 19 1997 T 164712 1 <NA> 314.00
#> 260 1 30 2008 W 126436 1 <NA> 890.00
#> 261 132 7 2008 W 126436 1 <NA> 1243.00
#> 262 26168 19 2008 T 164712 1 <NA> 1646.00
#> 263 58 9 1992 W 126436 1 <NA> 54.00
#> 264 238 44 2005 W 126436 1 U 2160.00
#> 265 <NA> 23 2005 T 164712 1 <NA> 630.00
#> 266 <NA> 34 2005 T 164712 1 <NA> 322.00
#> 267 138 65 1998 T 164712 1 <NA> 61.00
#> 268 78 85 1998 T 164712 1 <NA> 288.00
#> 269 207 15 1998 T 164712 1 <NA> 20.00
#> 270 58 27 1999 T 164712 1 <NA> 71.00
#> 271 54 25 1999 T 164712 1 <NA> 2.00
#> 272 50 71 1999 T 164712 1 <NA> 146.00
#> 273 151 88 1999 T 164712 1 <NA> 1976.00
#> 274 214 21 1999 T 164712 1 <NA> 476.00
#> 275 26182 32 2011 W 126436 1 U 2506.00
#> 276 <NA> 34 2003 T 164712 1 <NA> 6.00
#> 277 80 31 2003 T 164712 1 <NA> 128.00
#> 278 133 55 2002 T 164712 1 <NA> 107.00
#> 279 <NA> 7 2002 T 164712 1 <NA> 56.00
#> 280 15 15 2002 W 126436 1 <NA> 184.00
#> 281 67 28 1995 W 126436 1 <NA> 67.00
#> 282 000001 21 1995 W 126436 1 <NA> 221.00
#> 283 252 7 1995 W 126436 1 <NA> 700.00
#> 284 74 39 1994 T 164712 1 <NA> 457.00
#> 285 13 7 1993 W 126436 1 <NA> 1067.00
#> 286 02Feb 37 1993 W 126436 1 <NA> 12.00
#> 287 76 41 1991 W 126436 1 <NA> 125.00
#> 288 03Mar 19 1991 W 126436 1 <NA> 192.00
#> 289 24012 53 2004 T 164712 1 <NA> 5111.00
#> 290 696 21 2007 W 126436 1 U 1162.00
#> 291 25 68 1996 T 164712 1 <NA> 104.00
#> 292 25056 16 2009 W 126436 1 <NA> 662.00
#> 293 84 60 2005 W 126436 1 <NA> 292.00
#> 294 8 57 2005 W 126436 1 <NA> 616.00
#> 295 01Jan 15 1997 T 164712 1 <NA> 152.00
#> 296 64 30 1997 T 164712 1 <NA> 62.00
#> 297 03Mar 44 1997 T 164712 1 <NA> 8.00
#> 298 2 9 1997 T 164712 1 <NA> 485.00
#> 299 56 7 1992 W 126436 1 <NA> 188.00
#> 300 206 14 1998 T 164712 1 <NA> 194.00
#> 301 35 75 1998 T 164712 1 <NA> 850.00
#> 302 96 44 1999 T 164712 1 <NA> 108.00
#> 303 81 32 2003 T 164712 1 <NA> 72.00
#> 304 <NA> 66 2003 T 164712 1 <NA> 1040.00
#> 305 575 13 2002 W 126436 1 <NA> 1990.00
#> 306 60 9 1994 W 126436 1 <NA> 1022.00
#> 307 283 28 1994 W 126436 1 <NA> 268.00
#> 308 267 22 1995 W 126436 1 <NA> 2220.00
#> 309 60 17 2010 T 164712 1 <NA> 566.00
#> 310 85 37 1993 W 126436 1 <NA> 1332.00
#> 311 88 40 1993 W 126436 1 <NA> 633.00
#> 312 82 34 1993 W 126436 1 <NA> 399.00
#> 313 79 31 1993 W 126436 1 <NA> 378.00
#> 314 2 2 2004 W 126436 1 <NA> 286.00
#> 315 <NA> 8 2004 T 164712 1 <NA> 770.00
#> 316 83 46 1991 W 126436 1 <NA> 224.00
#> 317 2602 43 1991 W 126436 1 <NA> 120.00
#> 318 2604 44 1991 W 126436 1 <NA> 111.00
#> 319 69 84 2000 W 126436 1 <NA> 800.00
#> 320 30 15 2000 W 126436 1 <NA> 114.00
#> 321 237 34 2000 W 126436 1 <NA> 638.00
#> 322 83 49 2008 W 126436 1 <NA> 16.00
#> 323 51 23 2008 T 164712 1 <NA> 3344.00
#> 324 82 113 1996 W 126436 1 <NA> 422.00
#> 325 47 45 1996 T 164712 1 <NA> 176.00
#> 326 22 9 1997 T 164712 1 <NA> 19.00
#> 327 198 20 1997 W 126436 1 <NA> 66.00
#> 328 756 26 1997 W 126436 1 <NA> 22.00
#> 329 74 25 1992 W 126436 1 <NA> 2.00
#> 330 40 19 1998 T 164712 1 <NA> 6.00
#> 331 76 35 2001 T 164712 1 <NA> 108.00
#> 332 2 8 1999 T 164712 1 <NA> 1194.00
#> 333 39 42 2011 W 126436 1 <NA> 710.00
#> 334 8 4 2002 T 164712 1 <NA> 482.00
#> 335 574 12 2002 W 126436 1 <NA> 5076.00
#> 336 213 24 2010 W 126436 1 <NA> 2531.00
#> 337 76 25 1994 W 126436 1 <NA> 88.00
#> 338 265 10 1994 W 126436 1 <NA> 2960.00
#> 339 000001 23 1995 W 126436 1 <NA> 155.00
#> 340 82 30 1995 W 126436 1 <NA> 272.00
#> 341 85 37 1993 W 126436 1 <NA> 1332.00
#> 342 88 40 1993 W 126436 1 <NA> 633.00
#> 343 25 64 1993 T 164712 1 <NA> 818.00
#> 344 26132 24 2008 T 164712 1 <NA> 1696.00
#> 345 26182 14 2008 T 164712 1 <NA> 1638.00
#> 346 68 33 2000 W 126436 1 <NA> 23.00
#> 347 235 32 2000 W 126436 1 <NA> 636.00
#> 348 579 13 2000 W 126436 1 <NA> 742.00
#> 349 81 44 1991 W 126436 1 <NA> 164.00
#> 350 25232 67 1991 W 126436 1 <NA> 87.00
#> 351 20 25 2005 W 126436 1 <NA> 2212.00
#> 352 99 70 2005 W 126436 1 <NA> 444.00
#> 353 26 28 2005 W 126436 1 <NA> 1551.00
#> 354 131 6 2009 W 126436 1 <NA> 246.00
#> 355 <NA> 4 2009 W 126436 1 U 420.00
#> 356 76 41 1996 W 126436 1 <NA> 311.00
#> 357 57 31 1996 W 126436 1 <NA> 35.00
#> 358 65 35 1996 W 126436 1 <NA> 661.00
#> 359 77 26 1996 W 126436 1 <NA> 1088.00
#> 360 <NA> 40 1997 T 164712 1 <NA> 18.00
#> 361 2 13 1997 T 164712 1 <NA> 481.00
#> 362 91 43 1998 T 164712 1 <NA> 10.00
#> 363 138 65 1998 T 164712 1 <NA> 61.00
#> 364 <NA> 34 1998 T 164712 1 <NA> 290.00
#> 365 248 44 1998 T 164712 1 <NA> 1186.00
#> 366 01Jan 39 1998 T 164712 1 <NA> 48.00
#> 367 206 14 1998 T 164712 1 <NA> 194.00
#> 368 <NA> 16 1998 T 164712 1 <NA> 438.00
#> 369 731 29 1998 T 164712 1 <NA> 36.00
#> 370 8 4 2001 T 164712 1 <NA> 125.00
#> 371 56 27 2001 T 164712 1 <NA> 100.00
#> 372 72 33 2001 T 164712 1 <NA> 368.00
#> 373 671 33 1999 T 164712 1 <NA> 1440.00
#> 374 663 27 1999 T 164712 1 <NA> 1016.00
#> 375 13 6 2003 T 164712 1 <NA> 384.00
#> 376 38 43 2010 W 126436 1 <NA> 8645.51
#> 377 77 34 2002 T 164712 1 <NA> 617.00
#> 378 74 39 1994 T 164712 1 <NA> 457.00
#> 379 91 40 1994 W 126436 1 <NA> 1586.00
#> 380 252 23 2004 W 126436 1 U 78.00
#> 381 24300 51 2007 T 164712 1 <NA> 256.00
#> 382 283 41 2007 W 126436 1 <NA> 307.00
#> 383 <NA> 14 1995 W 126436 1 <NA> 516.00
#> 384 252 7 1995 W 126436 1 <NA> 700.00
#> 385 75 33 1993 W 126436 1 <NA> 600.00
#> 386 79 37 1993 W 126436 1 <NA> 248.00
#> 387 02Feb 48 1993 W 126436 1 <NA> 758.00
#> 388 02Feb 50 1993 W 126436 1 <NA> 162.00
#> 389 79 31 1993 W 126436 1 <NA> 378.00
#> 390 40 11 2012 W 126436 1 <NA> 1177.00
#> 391 158 79 2000 W 126436 1 <NA> 68.00
#> 392 30 15 2000 W 126436 1 <NA> 114.00
#> 393 <NA> 15 2000 W 126436 1 <NA> 2.00
#> 394 <NA> 30 2005 T 164712 1 <NA> 110.00
#> 395 266 37 2009 W 126436 1 <NA> 673.00
#> 396 274 40 2009 W 126436 1 <NA> 1228.00
#> 397 260 46 2009 W 126436 1 U 1190.00
#> 398 9 51 2009 W 126436 1 <NA> 1224.00
#> 399 <NA> 30 2009 W 126436 1 U 938.00
#> 400 223 18 1996 W 126436 1 <NA> 1232.00
#> 401 120 60 1991 W 126436 1 <NA> 108.00
#> 402 000001 11 1991 W 126436 1 <NA> 82.00
#> 403 000001 19 1991 W 126436 1 <NA> 282.00
#> 404 42 43 1991 T 164712 1 <NA> 34.00
#> 405 56 26 1997 T 164712 1 <NA> 59.00
#> 406 01Jan 22 1997 T 164712 1 <NA> 66.00
#> 407 <NA> 18 1997 T 164712 1 <NA> 100.00
#> 408 2 16 1997 T 164712 1 <NA> 335.00
#> 409 25 23 1992 T 164712 1 <NA> 1802.00
#> 410 113 4 2011 W 126436 1 <NA> 376.00
#> 411 80 39 1998 T 164712 1 <NA> 202.00
#> 412 66 69 1998 T 164712 1 <NA> 58.00
#> 413 130 61 1998 T 164712 1 <NA> 493.00
#> 414 205 13 1998 T 164712 1 <NA> 78.00
#> 415 03Mar 70 1999 T 164712 1 <NA> 118.00
#> 416 02Feb 9 1999 T 164712 1 <NA> 210.00
#> 417 198 7 1999 T 164712 1 <NA> 20.00
#> 418 60 16 2010 T 164712 1 <NA> 1578.00
#> 419 78 48 2010 W 126436 1 <NA> 549.00
#> 420 44 23 2003 T 164712 1 <NA> 43.00
#> 421 2024 27 2003 T 164712 1 <NA> 371.00
#> 422 219 2 2003 T 164712 1 <NA> 1968.00
#> 423 185 10 2002 T 164712 1 <NA> 1316.00
#> 424 180 5 2002 T 164712 1 <NA> 582.00
#> 425 588 22 2002 W 126436 1 <NA> 2018.00
#> 426 52 3 2007 T 164712 1 <NA> 972.00
#> 427 3 44 2007 W 126436 1 <NA> 981.00
#> 428 65 29 2006 W 126436 1 <NA> 1330.00
#> 429 81 48 2008 W 126436 1 <NA> 32.00
#> 430 26183 1 2008 T 164712 1 <NA> 508.00
#> 431 51 27 2008 T 164712 1 <NA> 192.00
#> 432 51 23 2008 T 164712 1 <NA> 3344.00
#> 433 000001 21 1995 W 126436 1 <NA> 221.00
#> 434 <NA> 31 1995 W 126436 1 <NA> 225.00
#> 435 64 12 1995 W 126436 1 <NA> 94.00
#> 436 25182 89 2014 W 126436 1 <NA> 795.00
#> 437 85 37 1993 W 126436 1 <NA> 1332.00
#> 438 18 23 2005 W 126436 1 <NA> 745.00
#> 439 4 4 2005 W 126436 1 <NA> 3199.00
#> 440 4 20 2005 W 126436 1 <NA> 773.00
#> 441 <NA> 30 2005 T 164712 1 <NA> 110.00
#> 442 25056 16 2009 W 126436 1 <NA> 662.00
#> 443 57 17 2009 T 164712 1 <NA> 165.00
#> 444 244 31 2009 W 126436 1 U 1574.00
#> 445 80 41 2000 T 164712 1 <NA> 466.00
#> 446 611 42 2000 W 126436 1 <NA> 206.00
#> 447 109 46 1996 W 126436 1 <NA> 44.00
#> 448 111 47 1996 W 126436 1 <NA> 78.00
#> 449 69 38 1996 W 126436 1 <NA> 118.00
#> 450 <NA> 23 1996 W 126436 1 <NA> 98.00
#> 451 73 22 1996 W 126436 1 <NA> 836.00
#> 452 99 48 1996 W 126436 1 <NA> 704.00
#> 453 72 1 1991 W 126436 1 <NA> 142.00
#> 454 69 37 1991 W 126436 1 <NA> 40.00
#> 455 75 40 1991 W 126436 1 <NA> 22.00
#> 456 81 44 1991 W 126436 1 <NA> 164.00
#> 457 82 45 1991 W 126436 1 <NA> 38.00
#> 458 26061 46 1991 W 126436 1 <NA> 129.00
#> 459 26071 48 1991 W 126436 1 <NA> 213.00
#> 460 2518 56 1991 W 126436 1 <NA> 173.00
#> 461 112 49 1997 T 164712 1 <NA> 196.00
#> 462 58 27 1997 T 164712 1 <NA> 185.00
#> 463 01Jan 43 1997 T 164712 1 <NA> 104.00
#> 464 24 10 1997 T 164712 1 <NA> 157.00
#> 465 03Mar 45 1997 T 164712 1 <NA> 14.00
#> 466 754 24 1997 W 126436 1 <NA> 418.00
#> 467 87 54 2011 W 126436 1 <NA> 2964.00
#> 468 26011 28 1992 W 126436 1 <NA> 37.00
#> 469 26022 40 1992 W 126436 1 <NA> 11.00
#> 470 105 49 1998 T 164712 1 <NA> 62.00
#> 471 28 13 1998 T 164712 1 <NA> 26.00
#> 472 130 61 1998 T 164712 1 <NA> 493.00
#> 473 <NA> 1 1998 T 164712 1 <NA> 34.00
#> 474 01Jan 17 1998 T 164712 1 <NA> 52.00
#> 475 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 476 <NA> 37 1998 T 164712 1 <NA> 668.00
#> 477 03Mar 59 1999 T 164712 1 <NA> 24.00
#> 478 24067 55 2010 W 126436 1 <NA> 1200.00
#> 479 24210 23 2010 W 126436 1 <NA> 523.00
#> 480 71 36 2003 T 164712 1 <NA> 255.00
#> 481 2024 27 2003 T 164712 1 <NA> 371.00
#> 482 774 15 2003 T 164712 1 <NA> 8.00
#> 483 <NA> 8 2003 T 164712 1 <NA> 780.00
#> 484 13 6 2003 T 164712 1 <NA> 384.00
#> 485 <NA> 64 2003 T 164712 1 <NA> 668.00
#> 486 13 6 2002 T 164712 1 <NA> 1229.00
#> 487 581 17 2002 W 126436 1 <NA> 790.00
#> 488 576 14 2002 W 126436 1 <NA> 1457.54
#> 489 283 41 2007 W 126436 1 <NA> 307.00
#> 490 46 25 2006 W 126436 1 <NA> 567.00
#> 491 <NA> 25 2006 W 126436 1 <NA> 20.00
#> 492 69 31 2006 W 126436 1 <NA> 289.00
#> 493 158 71 1994 T 164712 1 <NA> 147.00
#> 494 25 2 1994 T 164712 1 <NA> 72.00
#> 495 89 38 1994 W 126436 1 <NA> 260.00
#> 496 Jan 33 1994 T 164712 1 <NA> 138.00
#> 497 82 41 2004 W 126436 1 <NA> 32.00
#> 498 26132 24 2008 T 164712 1 <NA> 1696.00
#> 499 26168 19 2008 T 164712 1 <NA> 1646.00
#> 500 62 47 2012 W 126436 1 <NA> 1563.00
#> 501 172 14 2012 W 126436 1 <NA> 5641.00
#> 502 44 19 1995 W 126436 1 <NA> 45.00
#> 503 66 14 1995 W 126436 1 <NA> 124.00
#> 504 22 10 2005 W 126436 1 <NA> 717.00
#> 505 199 17 2009 W 126436 1 <NA> 558.00
#> 506 742 30 2009 W 126436 1 U 1696.00
#> 507 25052 17 2009 W 126436 1 U 1780.00
#> 508 45 55 2000 W 126436 1 <NA> 432.00
#> 509 <NA> 18 2000 W 126436 1 <NA> 1056.00
#> 510 212 14 2000 W 126436 1 <NA> 2610.00
#> 511 240 37 2000 W 126436 1 <NA> 2148.00
#> 512 50 65 2000 T 164712 1 <NA> 424.00
#> 513 11 6 1993 W 126436 1 <NA> 135.00
#> 514 95 43 1993 W 126436 1 <NA> 118.00
#> 515 02Feb 29 1993 W 126436 1 <NA> 50.00
#> 516 57 31 1996 W 126436 1 <NA> 35.00
#> 517 <NA> 13 1996 W 126436 1 <NA> 194.00
#> 518 78 27 1996 W 126436 1 <NA> 402.00
#> 519 01Jan 43 1997 T 164712 1 <NA> 104.00
#> 520 750 21 1997 W 126436 1 <NA> 58.00
#> 521 771 38 1997 W 126436 1 <NA> 28.00
#> 522 8 7 1991 W 126436 1 <NA> 13.00
#> 523 2407 30 1991 W 126436 1 <NA> 30.00
#> 524 25274 74 1991 W 126436 1 <NA> 28.00
#> 525 01Jan 26 1991 W 126436 1 <NA> 78.00
#> 526 175 16 2011 W 126436 1 <NA> 625.00
#> 527 62 30 2001 T 164712 1 <NA> 146.00
#> 528 73 34 2001 T 164712 1 <NA> 119.00
#> 529 82 57 1992 W 126436 1 <NA> 59.00
#> 530 26021 29 1992 W 126436 1 <NA> 68.00
#> 531 60 43 1992 W 126436 1 <NA> 72.00
#> 532 69 34 1998 T 164712 1 <NA> 154.00
#> 533 130 61 1998 T 164712 1 <NA> 493.00
#> 534 03Mar 67 1998 T 164712 1 <NA> 174.00
#> 535 249 45 1998 T 164712 1 <NA> 356.00
#> 536 223 27 1998 T 164712 1 <NA> 20.00
#> 537 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 538 30 73 1998 T 164712 1 <NA> 238.00
#> 539 03Mar 70 1999 T 164712 1 <NA> 118.00
#> 540 100030 18 1999 T 164712 1 <NA> 460.00
#> 541 663 27 1999 T 164712 1 <NA> 1016.00
#> 542 24312 24 2010 W 126436 1 <NA> 619.00
#> 543 143 8 2010 W 126436 1 <NA> 1646.00
#> 544 190 19 2010 W 126436 1 <NA> 1061.00
#> 545 213 24 2010 W 126436 1 <NA> 2531.00
#> 546 24 32 2010 W 126436 1 <NA> 904.00
#> 547 24237 31 2010 W 126436 1 <NA> 1098.00
#> 548 78 48 2010 W 126436 1 <NA> 549.00
#> 549 194 22 2010 W 126436 1 <NA> 697.00
#> 550 55 17 2010 T 164712 1 <NA> 1420.00
#> 551 25018 14 2007 T 164712 1 <NA> 724.00
#> 552 24 12 2003 T 164712 1 <NA> 229.00
#> 553 670 50 2003 T 164712 1 <NA> 67.00
#> 554 <NA> 2 2006 W 126436 1 <NA> 300.00
#> 555 <NA> 3 2006 W 126436 1 <NA> 70.00
#> 556 69 37 2006 W 126436 1 <NA> 448.00
#> 557 25173 18 2006 W 126436 1 <NA> 374.00
#> 558 58 43 2008 W 126436 1 <NA> 24.00
#> 559 185 22 2008 W 126436 1 <NA> 1532.00
#> 560 25061 15 2008 W 126436 1 <NA> 284.00
#> 561 25062 16 2008 W 126436 1 <NA> 372.00
#> 562 24142 28 2008 T 164712 1 <NA> 324.00
#> 563 132 7 2008 W 126436 1 <NA> 1243.00
#> 564 51 30 2008 T 164712 1 <NA> 280.00
#> 565 26168 19 2008 T 164712 1 <NA> 1646.00
#> 566 2 28 2008 W 126436 1 <NA> 2660.00
#> 567 24202 15 2004 T 164712 1 <NA> 5.00
#> 568 54 25 2004 W 126436 1 <NA> 414.00
#> 569 74 39 1994 T 164712 1 <NA> 457.00
#> 570 Mar 12 1994 T 164712 1 <NA> 130.00
#> 571 Mar 9 1994 T 164712 1 <NA> 128.00
#> 572 26020 34 2012 W 126436 1 U 488.00
#> 573 84 60 2005 W 126436 1 <NA> 292.00
#> 574 39 34 2005 W 126436 1 <NA> 251.00
#> 575 10 1 2005 W 126436 1 <NA> 551.00
#> 576 <NA> 46 2005 T 164712 1 <NA> 1526.00
#> 577 <NA> 26 2005 T 164712 1 <NA> 496.00
#> 578 <NA> 35 2005 T 164712 1 <NA> 734.00
#> 579 38 16 1995 W 126436 1 <NA> 240.00
#> 580 000001 23 1995 W 126436 1 <NA> 155.00
#> 581 94 42 1995 W 126436 1 <NA> 48.00
#> 582 <NA> 1 1995 W 126436 1 <NA> 414.00
#> 583 267 22 1995 W 126436 1 <NA> 2220.00
#> 584 252 7 1995 W 126436 1 <NA> 700.00
#> 585 262 35 2009 W 126436 1 <NA> 8840.00
#> 586 198 19 2009 W 126436 1 <NA> 2031.00
#> 587 266 37 2009 W 126436 1 <NA> 673.00
#> 588 57 33 2009 T 164712 1 <NA> 934.00
#> 589 259 45 2009 W 126436 1 U 3318.00
#> 590 9 51 2009 W 126436 1 <NA> 1224.00
#> 591 26169 6 2009 W 126436 1 U 1782.00
#> 592 64 81 2000 W 126436 1 <NA> 3920.00
#> 593 <NA> 5 2000 W 126436 1 <NA> 234.00
#> 594 <NA> 29 2000 W 126436 1 <NA> 162.00
#> 595 162 72 1993 W 126436 1 <NA> 128.00
#> 596 13 7 1993 W 126436 1 <NA> 1067.00
#> 597 000001 21 1993 W 126436 1 <NA> 3.00
#> 598 57 9 1993 W 126436 1 <NA> 108.00
#> 599 111 47 1996 W 126436 1 <NA> 78.00
#> 600 69 38 1996 W 126436 1 <NA> 118.00
#> 601 01Jan 30 1997 T 164712 1 <NA> 16.00
#> 602 <NA> 40 1997 T 164712 1 <NA> 18.00
#> 603 <NA> 26 1997 T 164712 1 <NA> 22.00
#> 604 744 15 1997 W 126436 1 <NA> 230.00
#> 605 754 24 1997 W 126436 1 <NA> 418.00
#> 606 66 49 2011 W 126436 1 <NA> 1309.00
#> 607 26182 32 2011 W 126436 1 U 2506.00
#> 608 173 15 2011 W 126436 1 <NA> 297.00
#> 609 122 62 1991 W 126436 1 <NA> 30.00
#> 610 76 41 1991 W 126436 1 <NA> 125.00
#> 611 80 43 1991 W 126436 1 <NA> 46.00
#> 612 2509 35 1991 W 126436 1 <NA> 191.00
#> 613 03Mar 3 1991 W 126436 1 <NA> 10.00
#> 614 01Jan 22 1991 W 126436 1 <NA> 12.00
#> 615 000003 12 1991 W 126436 1 <NA> 52.00
#> 616 611 19 2001 T 164712 1 <NA> 1210.00
#> 617 28 13 1998 T 164712 1 <NA> 26.00
#> 618 131 62 1998 T 164712 1 <NA> 105.00
#> 619 <NA> 36 1998 T 164712 1 <NA> 1424.00
#> 620 213 24 2010 W 126436 1 <NA> 2531.00
#> 621 87 38 1992 W 126436 1 <NA> 127.00
#> 622 21 11 1999 T 164712 1 <NA> 126.00
#> 623 25394 29 2007 W 126436 1 <NA> 1840.00
#> 624 167 14 2007 W 126436 1 <NA> 1885.17
#> 625 26044 7 2007 T 164712 1 <NA> 1233.00
#> 626 26182 8 2007 T 164712 1 <NA> 312.00
#> 627 55 30 2006 W 126436 1 <NA> 642.00
#> 628 <NA> 36 2006 W 126436 1 <NA> 62.00
#> 629 81 44 2006 W 126436 1 <NA> 1571.00
#> 630 25010 3 2008 T 164712 1 <NA> 120.00
#> 631 33 17 2003 T 164712 1 <NA> 498.00
#> 632 75 38 2003 T 164712 1 <NA> 77.00
#> 633 <NA> 54 2003 T 164712 1 <NA> 124.00
#> 634 <NA> 24 2003 T 164712 1 <NA> 210.00
#> 635 <NA> 22 2002 T 164712 1 <NA> 94.00
#> 636 <NA> 25 2002 T 164712 1 <NA> 262.00
#> 637 82 41 2004 W 126436 1 <NA> 32.00
#> 638 24 9 2004 W 126436 1 <NA> 117.00
#> 639 10 1 2004 W 126436 1 <NA> 82.00
#> 640 2 2 2004 W 126436 1 <NA> 286.00
#> 641 <NA> 1 2004 T 164712 1 <NA> 674.00
#> 642 <NA> 8 2004 T 164712 1 <NA> 770.00
#> 643 24202 38 2014 W 126436 1 <NA> 1245.00
#> 644 26133 31 2014 W 126436 1 U 1955.00
#> 645 4 4 2005 W 126436 1 <NA> 3199.00
#> 646 <NA> 21 2005 T 164712 1 <NA> 294.00
#> 647 <NA> 41 2005 T 164712 1 <NA> 1918.00
#> 648 36 43 2005 T 164712 1 <NA> 1030.00
#> 649 198 19 2009 W 126436 1 <NA> 2031.00
#> 650 175 13 2009 W 126436 1 <NA> 401.00
#> 651 24251 48 2009 T 164712 1 <NA> 528.00
#> 652 57 23 1995 W 126436 1 <NA> 223.00
#> 653 000001 19 1995 W 126436 1 <NA> 39.00
#> 654 84 32 1995 W 126436 1 <NA> 16.00
#> 655 235 32 2000 W 126436 1 <NA> 636.00
#> 656 48 22 1993 W 126436 1 <NA> 586.00
#> 657 59 11 1993 W 126436 1 <NA> 645.00
#> 658 80 32 1993 W 126436 1 <NA> 454.00
#> 659 77 29 1993 W 126436 1 <NA> 47.00
#> 660 43 23 1996 W 126436 1 <NA> 157.00
#> 661 34 11 1996 W 126436 1 <NA> 352.00
#> 662 <NA> 17 1996 W 126436 1 <NA> 405.00
#> 663 71 20 1996 W 126436 1 <NA> 904.00
#> 664 000001 62 1996 W 126436 1 <NA> 38.00
#> 665 78 27 1996 W 126436 1 <NA> 402.00
#> 666 36 16 1997 T 164712 1 <NA> 18.00
#> 667 754 24 1997 W 126436 1 <NA> 418.00
#> 668 66 49 2011 W 126436 1 <NA> 1309.00
#> 669 25039 16 2011 W 126436 1 U 1114.00
#> 670 1998 15 2001 T 164712 1 <NA> 124.00
#> 671 603 13 2001 T 164712 1 <NA> 432.00
#> 672 102 2 2010 W 126436 1 <NA> 727.00
#> 673 60 10 2010 T 164712 1 <NA> 1188.00
#> 674 60 17 2010 T 164712 1 <NA> 566.00
#> 675 26087 33 2010 W 126436 1 U 770.00
#> 676 242 42 2010 W 126436 1 U 78.00
#> 677 199 25 2010 W 126436 1 <NA> 1559.00
#> 678 142 11 2010 W 126436 1 <NA> 796.00
#> 679 166 16 2010 W 126436 1 <NA> 558.00
#> 680 46 30 1991 W 126436 1 <NA> 67.00
#> 681 72 1 1991 W 126436 1 <NA> 142.00
#> 682 76 41 1991 W 126436 1 <NA> 125.00
#> 683 2605 45 1991 W 126436 1 <NA> 196.00
#> 684 000001 17 1991 W 126436 1 <NA> 68.00
#> 685 25232 67 1991 W 126436 1 <NA> 87.00
#> 686 21 25 1991 W 126436 1 <NA> 24.00
#> 687 03Mar 2 1991 W 126436 1 <NA> 108.00
#> 688 03Mar 27 1991 W 126436 1 <NA> 4.00
#> 689 80 39 1998 T 164712 1 <NA> 202.00
#> 690 28 13 1998 T 164712 1 <NA> 26.00
#> 691 44 45 1998 T 164712 1 <NA> 596.00
#> 692 131 62 1998 T 164712 1 <NA> 105.00
#> 693 198 7 1998 T 164712 1 <NA> 1666.00
#> 694 03Mar 12 1998 T 164712 1 <NA> 18.00
#> 695 03Mar 63 1998 T 164712 1 <NA> 464.00
#> 696 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 697 <NA> 36 1998 T 164712 1 <NA> 1424.00
#> 698 52 1 2007 T 164712 1 <NA> 788.00
#> 699 283 41 2007 W 126436 1 <NA> 307.00
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#> 706 26021 29 1992 W 126436 1 <NA> 68.00
#> 707 78 54 1992 W 126436 1 <NA> 77.00
#> 708 85 59 1992 W 126436 1 <NA> 51.00
#> 709 83 58 1992 W 126436 1 <NA> 39.00
#> 710 81 32 1992 W 126436 1 <NA> 33.00
#> 711 71 22 1992 W 126436 1 <NA> 57.00
#> 712 58 9 1992 W 126436 1 <NA> 54.00
#> 713 26168 19 2008 T 164712 1 <NA> 1646.00
#> 714 106 49 1999 T 164712 1 <NA> 522.00
#> 715 104 48 1999 T 164712 1 <NA> 113.00
#> 716 44 69 1999 T 164712 1 <NA> 152.00
#> 717 82 139 1999 T 164712 1 <NA> 450.00
#> 718 198 7 1999 T 164712 1 <NA> 20.00
#> 719 653 18 1999 T 164712 1 <NA> 1058.00
#> 720 659 24 1999 T 164712 1 <NA> 364.00
#> 721 <NA> 57 2003 T 164712 1 <NA> 828.00
#> 722 750 40 2003 W 126436 1 <NA> 238.00
#> 723 85 39 2002 T 164712 1 <NA> 420.00
#> 724 70 34 2004 W 126436 1 <NA> 538.00
#> 725 52 26 1994 T 164712 1 <NA> 2.00
#> 726 74 39 1994 T 164712 1 <NA> 457.00
#> 727 65 14 1994 W 126436 1 <NA> 130.00
#> 728 49 40 2005 W 126436 1 <NA> 662.00
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#> 730 34 34 2005 W 126436 1 <NA> 2376.00
#> 731 33 33 2005 W 126436 1 <NA> 1598.00
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#> 736 24211 47 2009 T 164712 1 <NA> 229.00
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#> 738 26107 29 2009 W 126436 1 <NA> 472.00
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#> 743 24 12 2000 W 126436 1 <NA> 574.00
#> 744 160 81 2000 W 126436 1 <NA> 764.00
#> 745 270 47 2000 W 126436 1 <NA> 272.00
#> 746 240 37 2000 W 126436 1 <NA> 2148.00
#> 747 51 29 1996 W 126436 1 <NA> 212.00
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#> 755 000001 16 1993 W 126436 1 <NA> 171.00
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#> 761 173 15 2011 W 126436 1 <NA> 297.00
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#> 765 03Mar 59 1997 T 164712 1 <NA> 114.00
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#> 767 200 22 1997 W 126436 1 <NA> 32.00
#> 768 747 18 1997 W 126436 1 <NA> 932.00
#> 769 745 16 1997 W 126436 1 <NA> 47.65
#> 770 169 11 2010 W 126436 1 <NA> 1200.00
#> 771 243 34 2010 W 126436 1 <NA> 1276.00
#> 772 24210 23 2010 W 126436 1 <NA> 523.00
#> 773 60 17 2010 T 164712 1 <NA> 566.00
#> 774 60 29 2010 T 164712 1 <NA> 8274.00
#> 775 26211 1 2010 W 126436 1 U 248.00
#> 776 59 46 2010 W 126436 1 <NA> 582.00
#> 777 34 40 2010 W 126436 1 <NA> 554.00
#> 778 124 9 2010 W 126436 1 <NA> 199.00
#> 779 38 19 2001 T 164712 1 <NA> 2478.00
#> 780 50 25 2001 T 164712 1 <NA> 13.00
#> 781 26044 3 2007 W 126436 1 <NA> 528.00
#> 782 101 2 2007 W 126436 1 <NA> 1010.00
#> 783 283 41 2007 W 126436 1 <NA> 307.00
#> 784 130 7 2008 W 126436 1 <NA> 11.00
#> 785 49 2 2008 T 164712 1 <NA> 3033.00
#> 786 26182 14 2008 T 164712 1 <NA> 1638.00
#> 787 719 25 2008 W 126436 1 U 1332.00
#> 788 24020 38 2006 W 126436 1 <NA> 420.00
#> 789 26 14 2006 W 126436 1 <NA> 203.00
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#> 792 01Jan 46 1998 T 164712 1 <NA> 1096.00
#> 793 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 794 <NA> 37 1998 T 164712 1 <NA> 668.00
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#> 796 37 25 1991 W 126436 1 <NA> 192.00
#> 797 72 1 1991 W 126436 1 <NA> 142.00
#> 798 81 44 1991 W 126436 1 <NA> 164.00
#> 799 2605 45 1991 W 126436 1 <NA> 196.00
#> 800 01Jan 27 1991 W 126436 1 <NA> 58.00
#> 801 000003 14 1991 W 126436 1 <NA> 108.00
#> 802 61 89 1999 T 164712 1 <NA> 544.00
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#> 804 000001 5 1999 T 164712 1 <NA> 3.00
#> 805 100004 2 1999 T 164712 1 <NA> 2488.00
#> 806 658 23 1999 T 164712 1 <NA> 2784.00
#> 807 2 14 1999 T 164712 1 <NA> 2488.00
#> 808 2 8 1999 T 164712 1 <NA> 1194.00
#> 809 54 38 1992 W 126436 1 <NA> 97.00
#> 810 61 44 1992 W 126436 1 <NA> 26.00
#> 811 28063 32 1992 W 126436 1 <NA> 6.00
#> 812 71 22 1992 W 126436 1 <NA> 57.00
#> 813 29 10 2012 W 126436 1 <NA> 232.00
#> 814 42 12 2012 W 126436 1 <NA> 1180.00
#> 815 80 41 2003 T 164712 1 <NA> 436.00
#> 816 11 5 2003 T 164712 1 <NA> 283.00
#> 817 81 32 2003 T 164712 1 <NA> 72.00
#> 818 736 26 2003 W 126436 1 <NA> 340.00
#> 819 86 46 2013 W 126436 1 <NA> 284.00
#> 820 <NA> 28 2004 T 164712 1 <NA> 376.00
#> 821 133 55 2002 T 164712 1 <NA> 107.00
#> 822 109 43 2002 T 164712 1 <NA> 920.00
#> 823 16 16 2002 W 126436 1 <NA> 492.00
#> 824 <NA> 12 2002 T 164712 1 <NA> 1204.00
#> 825 42 20 2002 T 164712 1 <NA> 152.00
#> 826 64 33 1994 T 164712 1 <NA> 249.00
#> 827 82 31 1994 W 126436 1 <NA> 2875.24
#> 828 74 39 1994 T 164712 1 <NA> 457.00
#> 829 65 14 1994 W 126436 1 <NA> 130.00
#> 830 60 9 1994 W 126436 1 <NA> 1022.00
#> 831 Mar 5 1994 T 164712 1 <NA> 820.00
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#> 833 283 28 1994 W 126436 1 <NA> 268.00
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#> 835 1 30 2009 W 126436 1 <NA> 68.00
#> 836 24286 31 2009 T 164712 1 <NA> 339.00
#> 837 57 35 2009 T 164712 1 <NA> 360.00
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#> 839 26182 30 2009 W 126436 1 <NA> 1784.00
#> 840 129 5 2009 W 126436 1 <NA> 731.00
#> 841 27 37 2009 W 126436 1 <NA> 793.00
#> 842 24169 60 2009 T 164712 1 <NA> 105.00
#> 843 25013 18 2009 W 126436 1 U 766.00
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#> 845 8 2 1995 W 126436 1 <NA> 92.00
#> 846 31 18 1995 W 126436 1 <NA> 36.00
#> 847 80 91 1995 W 126436 1 <NA> 430.00
#> 848 <NA> 7 1995 W 126436 1 <NA> 248.00
#> 849 82 98 2000 W 126436 1 <NA> 120.00
#> 850 242 39 2000 W 126436 1 <NA> 266.00
#> 851 32 18 1996 W 126436 1 <NA> 1610.00
#> 852 65 35 1996 W 126436 1 <NA> 661.00
#> 853 03Mar 20 1996 W 126436 1 <NA> 66.00
#> 854 000001 64 1996 W 126436 1 <NA> 96.00
#> 855 57 6 1996 W 126436 1 <NA> 402.00
#> 856 229 24 1996 W 126436 1 <NA> 320.00
#> 857 87 54 2011 W 126436 1 <NA> 2964.00
#> 858 26182 32 2011 W 126436 1 U 2506.00
#> 859 56 18 2011 T 164712 1 <NA> 836.00
#> 860 173 15 2011 W 126436 1 <NA> 297.00
#> 861 232 26 2011 W 126436 1 <NA> 825.00
#> 862 17 9 1993 W 126436 1 <NA> 281.00
#> 863 85 37 1993 W 126436 1 <NA> 1332.00
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#> 866 01Jan 31 1997 T 164712 1 <NA> 162.00
#> 867 88 41 1997 T 164712 1 <NA> 797.00
#> 868 192 14 1997 W 126436 1 <NA> 224.00
#> 869 744 15 1997 W 126436 1 <NA> 230.00
#> 870 98 48 2010 W 126436 1 <NA> 646.00
#> 871 190 19 2010 W 126436 1 <NA> 1061.00
#> 872 207 20 2010 W 126436 1 <NA> 1955.00
#> 873 118 5 2010 W 126436 1 <NA> 675.00
#> 874 55 17 2010 T 164712 1 <NA> 1420.00
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#> 878 157 11 2008 W 126436 1 <NA> 51.00
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#> 880 24152 56 2007 T 164712 1 <NA> 70.00
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#> 882 55 35 2007 T 164712 1 <NA> 672.00
#> 883 131 54 2001 T 164712 1 <NA> 179.00
#> 884 19 10 2006 W 126436 1 <NA> 2456.00
#> 885 <NA> 29 2006 T 164712 1 <NA> 1786.00
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#> 887 130 61 1998 T 164712 1 <NA> 493.00
#> 888 44 21 1998 T 164712 1 <NA> 16.00
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#> 890 228 29 1998 T 164712 1 <NA> 54.00
#> 891 111 52 1999 T 164712 1 <NA> 420.00
#> 892 52 24 1999 T 164712 1 <NA> 31.00
#> 893 76 131 1999 T 164712 1 <NA> 328.00
#> 894 <NA> 31 1999 T 164712 1 <NA> 54.00
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#> 896 02Feb 25 1999 T 164712 1 <NA> 64.00
#> 897 269 69 1999 T 164712 1 <NA> 14.00
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#> 899 2604 44 1991 W 126436 1 <NA> 111.00
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#> 908 2511 24 1992 W 126436 1 <NA> 77.00
#> 909 26021 29 1992 W 126436 1 <NA> 68.00
#> 910 71 36 2003 T 164712 1 <NA> 255.00
#> 911 91 47 2003 T 164712 1 <NA> 448.00
#> 912 923 173 2002 T 164712 1 <NA> 1400.00
#> 913 195 20 2002 T 164712 1 <NA> 3166.00
#> 914 570 9 2002 W 126436 1 <NA> 410.00
#> 915 23 13 1994 T 164712 1 <NA> 208.00
#> 916 64 33 1994 T 164712 1 <NA> 249.00
#> 917 74 39 1994 T 164712 1 <NA> 457.00
#> 918 Mar 39 1994 T 164712 1 <NA> 192.00
#> 919 Mar 40 1994 T 164712 1 <NA> 637.00
#> 920 283 28 1994 W 126436 1 <NA> 268.00
#> 921 24041 46 2005 T 164712 1 <NA> 25.00
#> 922 34 34 2005 W 126436 1 <NA> 2376.00
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#> 930 78 48 2009 W 126436 1 <NA> 1077.00
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#> 944 24212 24 2011 W 126436 1 <NA> 147.00
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#> 947 59 95 1996 W 126436 1 <NA> 126.00
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#> 951 75 24 1996 W 126436 1 <NA> 3160.00
#> 952 198 20 1997 W 126436 1 <NA> 66.00
#> 953 2 19 1997 T 164712 1 <NA> 314.00
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#> 955 753 23 1997 W 126436 1 <NA> 2.00
#> 956 754 24 1997 W 126436 1 <NA> 418.00
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#> 958 85 37 1993 W 126436 1 <NA> 1332.00
#> 959 82 34 1993 W 126436 1 <NA> 399.00
#> 960 58 10 1993 W 126436 1 <NA> 85.00
#> 961 80 32 1993 W 126436 1 <NA> 454.00
#> 962 173 13 2010 W 126436 1 <NA> 260.00
#> 963 213 24 2010 W 126436 1 <NA> 2531.00
#> 964 24104 22 2010 W 126436 1 <NA> 570.00
#> 965 60 16 2010 T 164712 1 <NA> 1578.00
#> 966 60 23 2010 T 164712 1 <NA> 6475.00
#> 967 240 40 2010 W 126436 1 U 1082.00
#> 968 118 5 2010 W 126436 1 <NA> 675.00
#> 969 59 46 2010 W 126436 1 <NA> 582.00
#> 970 142 11 2010 W 126436 1 <NA> 796.00
#> 971 55 7 2010 T 164712 1 <NA> 1059.00
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#> 982 26132 1 2007 T 164712 1 <NA> 732.00
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#> 984 231 25 2001 W 126436 1 <NA> 162.00
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#> 987 83 37 2001 T 164712 1 F 42.00
#> 988 4 3 2001 T 164712 1 <NA> 1143.00
#> 989 66 49 2012 W 126436 1 <NA> 593.00
#> 990 <NA> 36 1998 T 164712 1 <NA> 1424.00
#> 991 25054 15 2013 W 126436 1 U 1621.00
#> 992 25051 12 2013 W 126436 1 U 3163.00
#> 993 229 3 2004 W 126436 1 U 70.00
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#> 1008 588 22 2002 W 126436 1 <NA> 2018.00
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#> 1021 2605 45 1991 W 126436 1 <NA> 196.00
#> 1022 26061 46 1991 W 126436 1 <NA> 129.00
#> 1023 53 43 2005 W 126436 1 <NA> 444.00
#> 1024 24071 50 2005 T 164712 1 <NA> 684.00
#> 1025 95 66 2005 W 126436 1 <NA> 764.00
#> 1026 224 32 2005 W 126436 1 U 1352.00
#> 1027 36 27 2005 T 164712 1 <NA> 116.00
#> 1028 25056 16 2009 W 126436 1 <NA> 662.00
#> 1029 57 2 2009 T 164712 1 <NA> 976.00
#> 1030 131 6 2009 W 126436 1 <NA> 246.00
#> 1031 250 28 2009 W 126436 1 <NA> 456.00
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#> 1034 50 25 2000 T 164712 1 <NA> 79.00
#> 1035 584 18 2000 W 126436 1 <NA> 454.00
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#> 1037 140 12 2011 W 126436 1 <NA> 2466.00
#> 1038 25173 19 2011 W 126436 1 U 1260.00
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#> 1050 28 15 1996 W 126436 1 <NA> 274.00
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#> 1055 95 44 1996 W 126436 1 <NA> 248.00
#> 1056 58 7 1996 W 126436 1 <NA> 4068.00
#> 1057 100 1 2010 W 126436 1 <NA> 552.00
#> 1058 124 5 2010 W 126436 1 <NA> 520.00
#> 1059 60 23 2010 T 164712 1 <NA> 6475.00
#> 1060 197 24 2010 W 126436 1 <NA> 585.00
#> 1061 124 9 2010 W 126436 1 <NA> 199.00
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#> 1063 24107 46 2008 T 164712 1 <NA> 384.00
#> 1064 26168 19 2008 T 164712 1 <NA> 1646.00
#> 1065 717 23 2008 W 126436 1 U 3988.39
#> 1066 51 23 2008 T 164712 1 <NA> 3344.00
#> 1067 18 7 1997 T 164712 1 <NA> 75.00
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#> 1069 201 23 1997 W 126436 1 <NA> 284.00
#> 1070 227 41 1997 W 126436 1 <NA> 16.00
#> 1071 197 19 1997 W 126436 1 <NA> 132.00
#> 1072 743 14 1997 W 126436 1 <NA> 526.00
#> 1073 2 16 1997 T 164712 1 <NA> 335.00
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#> 1076 25060 17 2007 W 126436 1 <NA> 740.00
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#> 1080 25175 17 2006 W 126436 1 <NA> 506.00
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#> 1084 41 13 1993 W 126436 1 <NA> 516.00
#> 1085 57 9 1993 W 126436 1 <NA> 108.00
#> 1086 252 21 1993 W 126436 1 <NA> 5932.00
#> 1087 38 19 2001 T 164712 1 <NA> 2478.00
#> 1088 220 40 2012 W 126436 1 <NA> 1946.00
#> 1089 40 11 2012 W 126436 1 <NA> 1177.00
#> 1090 36 30 2013 W 126436 1 <NA> 298.00
#> 1091 36 17 1998 T 164712 1 <NA> 44.00
#> 1092 03Mar 13 1998 T 164712 1 <NA> 24.00
#> 1093 03Mar 14 1998 T 164712 1 <NA> 384.00
#> 1094 03Mar 32 1998 T 164712 1 <NA> 248.00
#> 1095 191 3 1998 T 164712 1 <NA> 546.00
#> 1096 230 31 1998 T 164712 1 <NA> 6.00
#> 1097 <NA> 35 1998 T 164712 1 <NA> 1214.00
#> 1098 67 32 2004 W 126436 1 <NA> 775.00
#> 1099 <NA> 2 2003 T 164712 1 <NA> 34.00
#> 1100 <NA> 29 2003 T 164712 1 <NA> 80.00
#> 1101 733 23 2003 W 126436 1 <NA> 444.00
#> 1102 737 27 2003 W 126436 1 <NA> 297.00
#> 1103 <NA> 64 2003 T 164712 1 <NA> 668.00
#> 1104 50 23 1999 T 164712 1 <NA> 75.00
#> 1105 82 139 1999 T 164712 1 <NA> 450.00
#> 1106 000001 16 1999 T 164712 1 <NA> 8.00
#> 1107 663 27 1999 T 164712 1 <NA> 1016.00
#> 1108 13 6 2002 T 164712 1 <NA> 1229.00
#> 1109 577 15 2002 W 126436 1 <NA> 1919.67
#> 1110 574 12 2002 W 126436 1 <NA> 5076.00
#> 1111 108 10 2005 W 126436 1 <NA> 178.00
#> 1112 36 32 2005 T 164712 1 <NA> 1092.00
#> 1113 120 4 2009 W 126436 1 <NA> 782.00
#> 1114 271 54 2009 W 126436 1 U 658.00
#> 1115 26182 30 2009 W 126436 1 <NA> 1784.00
#> 1116 2501 47 1992 W 126436 1 <NA> 407.00
#> 1117 2509 22 1992 W 126436 1 <NA> 29.00
#> 1118 26021 29 1992 W 126436 1 <NA> 68.00
#> 1119 71 22 1992 W 126436 1 <NA> 57.00
#> 1120 55 4 1994 W 126436 1 <NA> 8.00
#> 1121 70 19 1994 W 126436 1 <NA> 18.00
#> 1122 153 70 1991 W 126436 1 <NA> 18.00
#> 1123 55 35 1991 W 126436 1 <NA> 82.00
#> 1124 72 1 1991 W 126436 1 <NA> 142.00
#> 1125 76 41 1991 W 126436 1 <NA> 125.00
#> 1126 80 43 1991 W 126436 1 <NA> 46.00
#> 1127 81 44 1991 W 126436 1 <NA> 164.00
#> 1128 000001 11 1991 W 126436 1 <NA> 82.00
#> 1129 26073 50 1991 W 126436 1 <NA> 77.00
#> 1130 000003 1 1991 W 126436 1 <NA> 90.00
#> 1131 000003 6 1991 W 126436 1 <NA> 16.00
#> 1132 01Jan 3 1991 W 126436 1 <NA> 70.00
#> 1133 000003 28 1991 W 126436 1 <NA> 119.00
#> 1134 03Mar 19 1991 W 126436 1 <NA> 192.00
#> 1135 28 14 2000 W 126436 1 <NA> 548.00
#> 1136 80 39 2000 W 126436 1 <NA> 43.00
#> 1137 <NA> 31 2000 W 126436 1 <NA> 278.00
#> 1138 240 37 2000 W 126436 1 <NA> 2148.00
#> 1139 87 44 2000 T 164712 1 <NA> 150.00
#> 1140 113 4 2011 W 126436 1 <NA> 376.00
#> 1141 25046 18 2011 W 126436 1 U 522.00
#> 1142 53 21 1995 W 126436 1 <NA> 26.00
#> 1143 000001 19 1995 W 126436 1 <NA> 39.00
#> 1144 <NA> 33 1995 W 126436 1 <NA> 87.00
#> 1145 80 28 1995 W 126436 1 <NA> 52.00
#> 1146 66 14 1995 W 126436 1 <NA> 124.00
#> 1147 31 17 1996 W 126436 1 <NA> 91.00
#> 1148 38 25 1996 W 126436 1 <NA> 144.00
#> 1149 43 35 1996 W 126436 1 <NA> 854.00
#> 1150 57 31 1996 W 126436 1 <NA> 35.00
#> 1151 <NA> 40 1996 W 126436 1 <NA> 598.00
#> 1152 <NA> 17 1996 W 126436 1 <NA> 405.00
#> 1153 01Jan 32 1996 W 126436 1 <NA> 90.00
#> 1154 227 22 1996 W 126436 1 <NA> 408.00
#> 1155 24002 19 2008 T 164712 1 <NA> 32.00
#> 1156 24183 49 2008 T 164712 1 <NA> 213.00
#> 1157 56 42 2008 W 126436 1 <NA> 8.00
#> 1158 49 7 2008 T 164712 1 <NA> 886.00
#> 1159 24321 24 2008 T 164712 1 <NA> 212.00
#> 1160 51 28 2008 T 164712 1 <NA> 1696.00
#> 1161 51 23 2008 T 164712 1 <NA> 3344.00
#> 1162 209 22 2010 W 126436 1 <NA> 1045.00
#> 1163 45 39 2010 W 126436 1 <NA> 945.00
#> 1164 26087 33 2010 W 126436 1 U 770.00
#> 1165 83 45 2006 W 126436 1 <NA> 463.00
#> 1166 240 46 2006 W 126436 1 U 1294.00
#> 1167 24 12 2007 W 126436 1 <NA> 860.00
#> 1168 26044 3 2007 W 126436 1 <NA> 528.00
#> 1169 3 44 2007 W 126436 1 <NA> 981.00
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#> 1171 2 16 1997 T 164712 1 <NA> 335.00
#> 1172 746 17 1997 W 126436 1 <NA> 468.00
#> 1173 745 16 1997 W 126436 1 <NA> 47.65
#> 1174 11 6 1993 W 126436 1 <NA> 135.00
#> 1175 162 72 1993 W 126436 1 <NA> 128.00
#> 1176 117 56 1993 W 126436 1 <NA> 203.00
#> 1177 40 12 1993 W 126436 1 <NA> 804.00
#> 1178 49 23 1993 W 126436 1 <NA> 1334.00
#> 1179 83 37 1993 W 126436 1 <NA> 8.00
#> 1180 85 37 1993 W 126436 1 <NA> 1332.00
#> 1181 55 7 1993 W 126436 1 <NA> 92.00
#> 1182 59 11 1993 W 126436 1 <NA> 645.00
#> 1183 67 19 1993 W 126436 1 <NA> 38.00
#> 1184 46 14 2012 W 126436 1 <NA> 788.00
#> 1185 <NA> 8 2001 T 164712 1 <NA> 384.00
#> 1186 248 39 2001 W 126436 1 <NA> 16.00
#> 1187 62 30 2001 T 164712 1 <NA> 146.00
#> 1188 20 10 2001 T 164712 1 <NA> 146.00
#> 1189 109 2 2013 W 126436 1 <NA> 874.00
#> 1190 24059 40 2013 W 126436 1 <NA> 8.00
#> 1191 228 2 2004 W 126436 1 U 3092.00
#> 1192 <NA> 13 2004 T 164712 1 <NA> 738.00
#> 1193 30 12 2004 W 126436 1 <NA> 257.00
#> 1194 59 27 2004 W 126436 1 <NA> 618.00
#> 1195 <NA> 60 2004 T 164712 1 <NA> 18.00
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#> 1197 130 61 1998 T 164712 1 <NA> 493.00
#> 1198 128 60 1998 T 164712 1 <NA> 114.00
#> 1199 03Mar 14 1998 T 164712 1 <NA> 384.00
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#> 1201 03Mar 63 1998 T 164712 1 <NA> 464.00
#> 1202 01Jan 46 1998 T 164712 1 <NA> 1096.00
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#> 1204 <NA> 27 1998 T 164712 1 <NA> 260.00
#> 1205 725 26 1998 T 164712 1 <NA> 240.00
#> 1206 233 41 2005 W 126436 1 U 574.00
#> 1207 36 35 2005 T 164712 1 <NA> 1442.00
#> 1208 24036 24 2003 T 164712 1 <NA> 303.00
#> 1209 49 26 2003 T 164712 1 <NA> 151.00
#> 1210 33 17 2003 T 164712 1 <NA> 498.00
#> 1211 <NA> 2 2003 T 164712 1 <NA> 34.00
#> 1212 26 12 2003 T 164712 1 <NA> 90.00
#> 1213 <NA> 54 2003 T 164712 1 <NA> 124.00
#> 1214 <NA> 3 2003 T 164712 1 <NA> 6.00
#> 1215 8 5 1999 T 164712 1 <NA> 19.00
#> 1216 663 27 1999 T 164712 1 <NA> 1016.00
#> 1217 479 179 2002 T 164712 1 <NA> 2062.00
#> 1218 <NA> 13 2002 T 164712 1 <NA> 90.00
#> 1219 45 22 2002 T 164712 1 <NA> 1272.00
#> 1220 574 12 2002 W 126436 1 <NA> 5076.00
#> 1221 107 1 2009 W 126436 1 <NA> 1719.00
#> 1222 131 6 2009 W 126436 1 <NA> 246.00
#> 1223 24288 55 2009 T 164712 1 <NA> 1959.00
#> 1224 741 29 2009 W 126436 1 U 2680.25
#> 1225 <NA> 4 2009 W 126436 1 U 420.00
#> 1226 25453 24 2009 W 126436 1 U 570.00
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#> 1229 65 14 1994 W 126436 1 <NA> 130.00
#> 1230 Mar 37 1994 T 164712 1 <NA> 584.00
#> 1231 70 19 1994 W 126436 1 <NA> 18.00
#> 1232 28 49 1994 T 164712 1 <NA> 86.00
#> 1233 283 28 1994 W 126436 1 <NA> 268.00
#> 1234 64 46 1992 W 126436 1 <NA> 25.00
#> 1235 82 57 1992 W 126436 1 <NA> 59.00
#> 1236 11 8 1992 W 126436 1 <NA> 17.00
#> 1237 78 54 1992 W 126436 1 <NA> 77.00
#> 1238 56 7 1992 W 126436 1 <NA> 188.00
#> 1239 49 31 1991 W 126436 1 <NA> 68.00
#> 1240 72 1 1991 W 126436 1 <NA> 142.00
#> 1241 76 41 1991 W 126436 1 <NA> 125.00
#> 1242 69 37 1991 W 126436 1 <NA> 40.00
#> 1243 81 44 1991 W 126436 1 <NA> 164.00
#> 1244 2512 38 1991 W 126436 1 <NA> 28.00
#> 1245 2602 43 1991 W 126436 1 <NA> 120.00
#> 1246 2605 45 1991 W 126436 1 <NA> 196.00
#> 1247 26062 47 1991 W 126436 1 <NA> 81.00
#> 1248 01Jan 1 1991 W 126436 1 <NA> 142.00
#> 1249 03Mar 19 1991 W 126436 1 <NA> 192.00
#> 1250 000003 15 1991 W 126436 1 <NA> 90.00
#> 1251 111 3 2011 W 126436 1 <NA> 564.00
#> 1252 56 24 2011 T 164712 1 <NA> 940.00
#> 1253 56 20 2011 T 164712 1 <NA> 608.00
#> 1254 24 30 2011 W 126436 1 <NA> 1002.00
#> 1255 25010 13 2011 W 126436 1 U 44.00
#> 1256 14 7 2000 W 126436 1 <NA> 135.00
#> 1257 243 40 2000 W 126436 1 <NA> 564.00
#> 1258 567 1 2000 W 126436 1 <NA> 380.00
#> 1259 24058 53 2008 T 164712 1 <NA> 10.00
#> 1260 24210 48 2008 T 164712 1 <NA> 182.00
#> 1261 24286 30 2008 T 164712 1 <NA> 1845.00
#> 1262 8 47 2008 W 126436 1 <NA> 517.00
#> 1263 49 2 2008 T 164712 1 <NA> 3033.00
#> 1264 1 27 2008 W 126436 1 <NA> 4582.00
#> 1265 155 10 2008 W 126436 1 <NA> 1446.00
#> 1266 26034 22 2008 T 164712 1 <NA> 306.00
#> 1267 26037 2 2008 T 164712 1 <NA> 1868.00
#> 1268 22 14 1995 W 126436 1 <NA> 124.00
#> 1269 <NA> 14 1995 W 126436 1 <NA> 516.00
#> 1270 02Feb 90 1995 W 126436 1 <NA> 69.00
#> 1271 56 4 1995 W 126436 1 <NA> 1038.00
#> 1272 257 12 1995 W 126436 1 <NA> 1800.00
#> 1273 250 5 1995 W 126436 1 <NA> 102.00
#> 1274 74 44 2010 W 126436 1 <NA> 696.00
#> 1275 175 14 2010 W 126436 1 <NA> 1426.00
#> 1276 210 23 2010 W 126436 1 <NA> 655.00
#> 1277 227 28 2010 W 126436 1 <NA> 2480.00
#> 1278 60 10 2010 T 164712 1 <NA> 1188.00
#> 1279 26211 1 2010 W 126436 1 U 248.00
#> 1280 78 48 2010 W 126436 1 <NA> 549.00
#> 1281 118 5 2010 W 126436 1 <NA> 675.00
#> 1282 672 4 2010 W 126436 1 U 2651.09
#> 1283 61 33 1996 W 126436 1 <NA> 1867.00
#> 1284 14 7 1996 W 126436 1 <NA> 64.00
#> 1285 41 31 1996 W 126436 1 <NA> 1178.00
#> 1286 68 87 1996 W 126436 1 <NA> 122.00
#> 1287 30 16 1996 W 126436 1 <NA> 1965.00
#> 1288 <NA> 8 1996 W 126436 1 <NA> 925.00
#> 1289 <NA> 13 1996 W 126436 1 <NA> 194.00
#> 1290 000001 86 1996 W 126436 1 <NA> 60.00
#> 1291 78 27 1996 W 126436 1 <NA> 402.00
#> 1292 61 10 1996 W 126436 1 <NA> 858.00
#> 1293 69 18 1996 W 126436 1 <NA> 1248.00
#> 1294 229 24 1996 W 126436 1 <NA> 320.00
#> 1295 234 29 1996 W 126436 1 <NA> 34.00
#> 1296 46 25 2006 W 126436 1 <NA> 567.00
#> 1297 25173 13 2006 T 164712 1 <NA> 718.00
#> 1298 <NA> 29 2006 T 164712 1 <NA> 1786.00
#> 1299 7 32 2006 W 126436 1 <NA> 234.00
#> 1300 108 5 2007 W 126436 1 <NA> 1410.00
#> 1301 12 6 2007 W 126436 1 <NA> 859.00
#> 1302 52 3 2007 T 164712 1 <NA> 972.00
#> 1303 52 14 2007 T 164712 1 <NA> 4366.00
#> 1304 26015 34 2007 W 126436 1 <NA> 112.00
#> 1305 25212 15 2007 T 164712 1 <NA> 614.00
#> 1306 25177 29 2007 T 164712 1 <NA> 536.00
#> 1307 01Jan 13 1997 T 164712 1 <NA> 520.00
#> 1308 20 8 1997 T 164712 1 <NA> 39.00
#> 1309 198 20 1997 W 126436 1 <NA> 66.00
#> 1310 216 32 1997 W 126436 1 <NA> 10.00
#> 1311 224 40 1997 W 126436 1 <NA> 1122.00
#> 1312 2 16 1997 T 164712 1 <NA> 335.00
#> 1313 738 9 1997 W 126436 1 <NA> 16.00
#> 1314 2 11 1997 T 164712 1 <NA> 6.00
#> 1315 42 12 2012 W 126436 1 <NA> 1180.00
#> 1316 34 17 2001 T 164712 1 <NA> 315.00
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#> 1318 73 34 2001 T 164712 1 <NA> 119.00
#> 1319 159 69 1993 W 126436 1 <NA> 51.00
#> 1320 40 12 1993 W 126436 1 <NA> 804.00
#> 1321 51 19 1993 W 126436 1 <NA> 264.00
#> 1322 79 37 1993 W 126436 1 <NA> 248.00
#> 1323 53 5 1993 W 126436 1 <NA> 2142.00
#> 1324 <NA> 62 2004 T 164712 1 <NA> 164.00
#> 1325 130 61 1998 T 164712 1 <NA> 493.00
#> 1326 128 60 1998 T 164712 1 <NA> 114.00
#> 1327 114 53 1998 T 164712 1 <NA> 221.00
#> 1328 03Mar 14 1998 T 164712 1 <NA> 384.00
#> 1329 01Jan 22 1998 T 164712 1 <NA> 28.00
#> 1330 03Mar 63 1998 T 164712 1 <NA> 464.00
#> 1331 249 45 1998 T 164712 1 <NA> 356.00
#> 1332 205 13 1998 T 164712 1 <NA> 78.00
#> 1333 204 12 1998 T 164712 1 <NA> 26.00
#> 1334 <NA> 33 1998 T 164712 1 <NA> 302.00
#> 1335 33 33 2005 W 126436 1 <NA> 1598.00
#> 1336 <NA> 49 2005 T 164712 1 <NA> 51.00
#> 1337 42 22 2003 T 164712 1 <NA> 145.00
#> 1338 77 39 2003 T 164712 1 <NA> 277.00
#> 1339 179 15 2009 W 126436 1 <NA> 539.00
#> 1340 116 2 2009 W 126436 1 <NA> 1636.00
#> 1341 24150 33 2009 T 164712 1 <NA> 470.00
#> 1342 57 17 2009 T 164712 1 <NA> 165.00
#> 1343 24125 56 2009 T 164712 1 <NA> 885.00
#> 1344 133 7 2009 W 126436 1 <NA> 162.00
#> 1345 24263 34 2009 T 164712 1 <NA> 148.00
#> 1346 109 43 2002 T 164712 1 <NA> 920.00
#> 1347 7 7 2002 W 126436 1 <NA> 2344.00
#> 1348 180 5 2002 T 164712 1 <NA> 582.00
#> 1349 26 13 1999 T 164712 1 <NA> 757.00
#> 1350 52 24 1999 T 164712 1 <NA> 31.00
#> 1351 201 10 1999 T 164712 1 <NA> 1374.00
#> 1352 03Mar 55 1999 T 164712 1 <NA> 170.00
#> 1353 000001 16 1999 T 164712 1 <NA> 8.00
#> 1354 207 15 1999 T 164712 1 <NA> 514.00
#> 1355 671 33 1999 T 164712 1 <NA> 1440.00
#> 1356 664 28 1999 T 164712 1 <NA> 186.00
#> 1357 83 56 1994 T 164712 1 <NA> 501.00
#> 1358 1 1 1994 T 164712 1 <NA> 68.00
#> 1359 74 39 1994 T 164712 1 <NA> 457.00
#> 1360 60 9 1994 W 126436 1 <NA> 1022.00
#> 1361 58 7 1994 W 126436 1 <NA> 20.00
#> 1362 55 4 1994 W 126436 1 <NA> 8.00
#> 1363 56 40 1992 W 126436 1 <NA> 21.00
#> 1364 26021 29 1992 W 126436 1 <NA> 68.00
#> 1365 2810 36 1992 W 126436 1 <NA> 15.00
#> 1366 85 59 1992 W 126436 1 <NA> 51.00
#> 1367 83 58 1992 W 126436 1 <NA> 39.00
#> 1368 15 12 1991 W 126436 1 <NA> 151.00
#> 1369 45 29 1991 W 126436 1 <NA> 91.00
#> 1370 49 31 1991 W 126436 1 <NA> 68.00
#> 1371 76 41 1991 W 126436 1 <NA> 125.00
#> 1372 75 40 1991 W 126436 1 <NA> 22.00
#> 1373 81 44 1991 W 126436 1 <NA> 164.00
#> 1374 2507 34 1991 W 126436 1 <NA> 40.00
#> 1375 25132 40 1991 W 126436 1 <NA> 375.00
#> 1376 25151 51 1991 W 126436 1 <NA> 121.00
#> 1377 2517 55 1991 W 126436 1 <NA> 64.00
#> 1378 000001 17 1991 W 126436 1 <NA> 68.00
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#> 1380 66 49 2011 W 126436 1 <NA> 1309.00
#> 1381 151 13 2011 W 126436 1 <NA> 1708.00
#> 1382 25051 16 2011 W 126436 1 U 330.00
#> 1383 251 45 2000 W 126436 1 <NA> 102.00
#> 1384 238 35 2000 W 126436 1 <NA> 2056.00
#> 1385 87 44 2000 T 164712 1 <NA> 150.00
#> 1386 189 24 2008 W 126436 1 <NA> 2877.00
#> 1387 2 27 2008 W 126436 1 <NA> 532.00
#> 1388 26057 5 2008 T 164712 1 <NA> 154.00
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#> 1390 26183 1 2008 T 164712 1 <NA> 508.00
#> 1391 26020 18 2008 T 164712 1 <NA> 2366.00
#> 1392 26168 19 2008 T 164712 1 <NA> 1646.00
#> 1393 730 32 2008 W 126436 1 U 744.00
#> 1394 173 13 2010 W 126436 1 <NA> 260.00
#> 1395 207 20 2010 W 126436 1 <NA> 1955.00
#> 1396 213 24 2010 W 126436 1 <NA> 2531.00
#> 1397 24104 22 2010 W 126436 1 <NA> 570.00
#> 1398 60 16 2010 T 164712 1 <NA> 1578.00
#> 1399 60 18 2010 T 164712 1 <NA> 3134.00
#> 1400 60 34 2010 T 164712 1 <NA> 2815.00
#> 1401 221 29 2010 W 126436 1 <NA> 1398.00
#> 1402 55 6 2010 T 164712 1 <NA> 1138.00
#> 1403 673 5 2010 W 126436 1 U 2348.67
#> 1404 30 16 2006 W 126436 1 <NA> 111.00
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#> 1409 25394 29 2007 W 126436 1 <NA> 1840.00
#> 1410 24210 26 2007 T 164712 1 <NA> 551.00
#> 1411 25453 10 2007 T 164712 1 <NA> 764.00
#> 1412 24171 50 2019 W 126436 1 <NA> 177.00
#> 1413 33 14 1995 W 126436 1 <NA> 32.00
#> 1414 000001 10 1995 W 126436 1 <NA> 84.00
#> 1415 92 40 1995 W 126436 1 <NA> 12.00
#> 1416 <NA> 1 1995 W 126436 1 <NA> 414.00
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#> 1418 265 20 1995 W 126436 1 <NA> 1026.00
#> 1419 252 7 1995 W 126436 1 <NA> 700.00
#> 1420 26 46 1995 T 164712 1 <NA> 496.00
#> 1421 254 9 1995 W 126436 1 <NA> 274.00
#> 1422 246 1 1995 W 126436 1 <NA> 2698.00
#> 1423 261 16 1995 W 126436 1 <NA> 136.00
#> 1424 250 5 1995 W 126436 1 <NA> 102.00
#> 1425 28 23 1996 W 126436 1 <NA> 64.00
#> 1426 32 7 1996 W 126436 1 <NA> 626.00
#> 1427 34 11 1996 W 126436 1 <NA> 352.00
#> 1428 <NA> 18 1996 W 126436 1 <NA> 200.00
#> 1429 93 42 1996 W 126436 1 <NA> 116.00
#> 1430 95 44 1996 W 126436 1 <NA> 248.00
#> 1431 90 39 1996 W 126436 1 <NA> 50.00
#> 1432 78 27 1996 W 126436 1 <NA> 402.00
#> 1433 234 29 1996 W 126436 1 <NA> 34.00
#> 1434 216 11 1996 W 126436 1 <NA> 981.60
#> 1435 24016 18 2016 W 126436 1 <NA> 23.00
#> 1436 01Jan 13 1997 T 164712 1 <NA> 520.00
#> 1437 01Jan 20 1997 T 164712 1 <NA> 18.00
#> 1438 03Mar 18 1997 T 164712 1 <NA> 54.00
#> 1439 743 14 1997 W 126436 1 <NA> 526.00
#> 1440 768 35 1997 W 126436 1 <NA> 14.00
#> 1441 662 41 2001 T 164712 1 <NA> 604.00
#> 1442 247 38 2001 W 126436 1 <NA> 375.00
#> 1443 <NA> 56 2001 T 164712 1 <NA> 39.00
#> 1444 204 1 2001 W 126436 1 <NA> 2262.00
#> 1445 610 18 2001 T 164712 1 <NA> 870.00
#> 1446 624 27 2001 T 164712 1 <NA> 790.00
#> 1447 627 29 2001 T 164712 1 <NA> 220.00
#> 1448 41 19 1993 W 126436 1 <NA> 178.00
#> 1449 28 11 2004 W 126436 1 <NA> 126.00
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#> 1452 24286 44 2005 T 164712 1 <NA> 856.00
#> 1453 <NA> 52 2005 T 164712 1 <NA> 534.00
#> 1454 612 13 2005 T 164712 1 U 2685.00
#> 1455 36 32 2005 T 164712 1 <NA> 1092.00
#> 1456 <NA> 13 2005 T 164712 1 <NA> 798.00
#> 1457 66 69 1998 T 164712 1 <NA> 58.00
#> 1458 128 60 1998 T 164712 1 <NA> 114.00
#> 1459 118 55 1998 T 164712 1 <NA> 34.00
#> 1460 01Jan 17 1998 T 164712 1 <NA> 52.00
#> 1461 231 32 1998 T 164712 1 <NA> 416.00
#> 1462 <NA> 37 1998 T 164712 1 <NA> 668.00
#> 1463 703 9 1998 T 164712 1 <NA> 922.00
#> 1464 29 68 1998 T 164712 1 <NA> 416.00
#> 1465 24283 37 2009 T 164712 1 <NA> 702.00
#> 1466 116 2 2009 W 126436 1 <NA> 1636.00
#> 1467 57 15 2009 T 164712 1 <NA> 224.00
#> 1468 111 3 2009 W 126436 1 <NA> 2698.00
#> 1469 131 6 2009 W 126436 1 <NA> 246.00
#> 1470 137 9 2009 W 126436 1 <NA> 2575.00
#> 1471 199 17 2009 W 126436 1 <NA> 558.00
#> 1472 86 44 2003 T 164712 1 <NA> 265.00
#> 1473 49 24 2003 T 164712 1 <NA> 89.00
#> 1474 <NA> 57 2003 T 164712 1 <NA> 828.00
#> 1475 20 20 2002 W 126436 1 <NA> 68.00
#> 1476 2 2 1999 T 164712 1 <NA> 42.00
#> 1477 99 46 1999 T 164712 1 <NA> 258.00
#> 1478 2 2 1994 T 164712 1 <NA> 31.00
#> 1479 56 5 1994 W 126436 1 <NA> 830.00
#> 1480 74 39 1994 T 164712 1 <NA> 457.00
#> 1481 83 32 1994 W 126436 1 <NA> 524.00
#> 1482 283 28 1994 W 126436 1 <NA> 268.00
#> 1483 2516 18 1992 W 126436 1 <NA> 116.00
#> 1484 61 44 1992 W 126436 1 <NA> 26.00
#> 1485 26011 28 1992 W 126436 1 <NA> 37.00
#> 1486 26021 29 1992 W 126436 1 <NA> 68.00
#> 1487 2810 36 1992 W 126436 1 <NA> 15.00
#> 1488 87 38 1992 W 126436 1 <NA> 127.00
#> 1489 71 22 1992 W 126436 1 <NA> 57.00
#> 1490 88 39 1992 W 126436 1 <NA> 149.00
#> 1491 58 9 1992 W 126436 1 <NA> 54.00
#> 1492 56 7 1992 W 126436 1 <NA> 188.00
#> 1493 87 54 2011 W 126436 1 <NA> 2964.00
#> 1494 24324 48 2011 W 126436 1 <NA> 583.00
#> 1495 26182 32 2011 W 126436 1 U 2506.00
#> 1496 25173 19 2011 W 126436 1 U 1260.00
#> 1497 175 16 2011 W 126436 1 <NA> 625.00
#> 1498 74 14 2014 W 126436 1 <NA> 625.00
#> 1499 24306 25 2008 T 164712 1 <NA> 455.00
#> 1500 24316 41 2008 T 164712 1 <NA> 864.00
#> 1501 30 35 2008 W 126436 1 <NA> 48.00
#> 1502 25061 15 2008 W 126436 1 <NA> 284.00
#> 1503 243 48 2008 W 126436 1 U 3128.00
#> 1504 26132 24 2008 T 164712 1 <NA> 1696.00
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#> 1507 36 24 1991 W 126436 1 <NA> 41.00
#> 1508 50 32 1991 W 126436 1 <NA> 293.00
#> 1509 71 39 1991 W 126436 1 <NA> 54.00
#> 1510 72 1 1991 W 126436 1 <NA> 142.00
#> 1511 76 41 1991 W 126436 1 <NA> 125.00
#> 1512 2604 44 1991 W 126436 1 <NA> 111.00
#> 1513 2605 45 1991 W 126436 1 <NA> 196.00
#> 1514 000003 19 1991 W 126436 1 <NA> 124.00
#> 1515 000003 21 1991 W 126436 1 <NA> 70.00
#> 1516 01Jan 3 1991 W 126436 1 <NA> 70.00
#> 1517 589 23 2000 W 126436 1 <NA> 1688.00
#> 1518 100 1 2010 W 126436 1 <NA> 552.00
#> 1519 74 44 2010 W 126436 1 <NA> 696.00
#> 1520 213 24 2010 W 126436 1 <NA> 2531.00
#> 1521 214 25 2010 W 126436 1 <NA> 928.00
#> 1522 45 39 2010 W 126436 1 <NA> 945.00
#> 1523 60 18 2010 T 164712 1 <NA> 3134.00
#> 1524 26087 33 2010 W 126436 1 U 770.00
#> 1525 1 30 2010 W 126436 1 <NA> 11984.00
#> 1526 78 48 2010 W 126436 1 <NA> 549.00
#> 1527 118 5 2010 W 126436 1 <NA> 675.00
#> 1528 57 45 2010 W 126436 1 <NA> 1602.00
#> 1529 166 16 2010 W 126436 1 <NA> 558.00
#> 1530 108 3 2010 W 126436 1 <NA> 1062.00
#> 1531 55 17 2010 T 164712 1 <NA> 1420.00
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#> 1536 52 1 2007 T 164712 1 <NA> 788.00
#> 1537 283 41 2007 W 126436 1 <NA> 307.00
#> 1538 3 44 2007 W 126436 1 <NA> 981.00
#> 1539 697 22 2007 W 126436 1 U 1500.00
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#> 1541 46 26 1996 W 126436 1 <NA> 110.00
#> 1542 27 131 1996 W 126436 1 <NA> 102.00
#> 1543 45 25 1996 W 126436 1 <NA> 93.00
#> 1544 57 31 1996 W 126436 1 <NA> 35.00
#> 1545 <NA> 18 1996 W 126436 1 <NA> 200.00
#> 1546 <NA> 16 1996 W 126436 1 <NA> 266.00
#> 1547 <NA> 26 1996 W 126436 1 <NA> 66.00
#> 1548 95 44 1996 W 126436 1 <NA> 248.00
#> 1549 03Mar 18 1996 W 126436 1 <NA> 214.00
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#> 1551 224 19 1996 W 126436 1 <NA> 398.00
#> 1552 235 30 1996 W 126436 1 <NA> 396.00
#> 1553 8 2 1995 W 126436 1 <NA> 92.00
#> 1554 45 45 1995 W 126436 1 <NA> 2079.00
#> 1555 38 16 1995 W 126436 1 <NA> 240.00
#> 1556 40 17 1995 W 126436 1 <NA> 280.00
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#> 1559 75 23 1995 W 126436 1 <NA> 496.00
#> 1560 98 46 1995 W 126436 1 <NA> 1236.00
#> 1561 89 52 2012 W 126436 1 <NA> 449.00
#> 1562 91 53 2012 W 126436 1 <NA> 301.00
#> 1563 26217 37 2012 W 126436 1 U 5043.00
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#> 1567 03Mar 16 1997 T 164712 1 <NA> 20.00
#> 1568 214 30 1997 W 126436 1 <NA> 134.00
#> 1569 224 40 1997 W 126436 1 <NA> 1122.00
#> 1570 194 16 1997 W 126436 1 <NA> 608.00
#> 1571 196 18 1997 W 126436 1 <NA> 1118.00
#> 1572 2 20 1997 T 164712 1 <NA> 146.00
#> 1573 162 17 2013 W 126436 1 <NA> 1666.00
#> 1574 25054 15 2013 W 126436 1 U 1621.00
#> 1575 3337 81 2001 T 164712 1 <NA> 74.00
#> 1576 84 41 2001 T 164712 1 <NA> 130.00
#> 1577 21 21 2001 W 126436 1 <NA> 36.00
#> 1578 35 35 2001 W 126436 1 <NA> 246.00
#> 1579 610 18 2001 T 164712 1 <NA> 870.00
#> 1580 602 12 2001 T 164712 1 <NA> 40.00
#> 1581 22 8 2004 W 126436 1 <NA> 522.00
#> 1582 70 34 2004 W 126436 1 <NA> 538.00
#> 1583 1 7 2004 T 164712 1 <NA> 194.00
#> 1584 32 32 2004 W 126436 1 <NA> 372.00
#> 1585 260 30 2004 W 126436 1 U 270.00
#> 1586 54 25 2004 W 126436 1 <NA> 414.00
#> 1587 <NA> 11 2005 T 164712 1 <NA> 404.00
#> 1588 <NA> 23 2005 T 164712 1 <NA> 630.00
#> 1589 <NA> 15 2005 T 164712 1 <NA> 758.00
#> 1590 43 15 1993 W 126436 1 <NA> 210.00
#> 1591 50 17 1993 W 126436 1 <NA> 280.00
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#> 1593 79 31 1993 W 126436 1 <NA> 378.00
#> 1594 80 32 1993 W 126436 1 <NA> 454.00
#> 1595 29 45 1993 T 164712 1 <NA> 108.00
#> 1596 120 4 2009 W 126436 1 <NA> 782.00
#> 1597 25056 16 2009 W 126436 1 <NA> 662.00
#> 1598 142 8 2009 W 126436 1 <NA> 826.00
#> 1599 57 3 2009 T 164712 1 <NA> 916.00
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#> 1602 57 20 2009 T 164712 1 <NA> 452.00
#> 1603 26137 28 2009 W 126436 1 <NA> 252.00
#> 1604 131 6 2009 W 126436 1 <NA> 246.00
#> 1605 737 25 2009 W 126436 1 U 544.00
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#> 1607 122 57 1998 T 164712 1 <NA> 44.00
#> 1608 44 21 1998 T 164712 1 <NA> 16.00
#> 1609 114 53 1998 T 164712 1 <NA> 221.00
#> 1610 01Jan 8 1998 T 164712 1 <NA> 22.00
#> 1611 228 29 1998 T 164712 1 <NA> 54.00
#> 1612 <NA> 27 1998 T 164712 1 <NA> 260.00
#> 1613 703 9 1998 T 164712 1 <NA> 922.00
#> 1614 704 10 1998 T 164712 1 <NA> 476.00
#> 1615 720 22 1998 T 164712 1 <NA> 208.00
#> 1616 725 26 1998 T 164712 1 <NA> 240.00
#> 1617 77 39 2003 T 164712 1 <NA> 277.00
#> 1618 227 8 2003 T 164712 1 <NA> 2070.00
#> 1619 228 9 2003 T 164712 1 <NA> 586.00
#> 1620 32 15 2003 T 164712 1 <NA> 116.00
#> 1621 45 22 2003 T 164712 1 <NA> 93.00
#> 1622 <NA> 56 2003 T 164712 1 <NA> 296.00
#> 1623 <NA> 32 2002 T 164712 1 <NA> 1166.00
#> 1624 186 11 2002 T 164712 1 <NA> 416.00
#> 1625 45 22 2002 T 164712 1 <NA> 1272.00
#> 1626 <NA> 5 1999 T 164712 1 <NA> 94.00
#> 1627 671 33 1999 T 164712 1 <NA> 1440.00
#> 1628 46 23 1994 T 164712 1 <NA> 58.00
#> 1629 83 32 1994 W 126436 1 <NA> 524.00
#> 1630 269 14 1994 W 126436 1 <NA> 2566.00
#> 1631 273 18 1994 W 126436 1 <NA> 170.00
#> 1632 283 28 1994 W 126436 1 <NA> 268.00
#> 1633 264 9 1994 W 126436 1 <NA> 4318.00
#> 1634 113 4 2011 W 126436 1 <NA> 376.00
#> 1635 232 30 2011 W 126436 1 <NA> 450.00
#> 1636 56 23 2011 T 164712 1 <NA> 1542.00
#> 1637 26191 4 2011 W 126436 1 U 1757.00
#> 1638 54 38 1992 W 126436 1 <NA> 97.00
#> 1639 2503 15 1992 W 126436 1 <NA> 100.00
#> 1640 25081 21 1992 W 126436 1 <NA> 64.00
#> 1641 18 13 1992 W 126436 1 <NA> 19.00
#> 1642 26021 29 1992 W 126436 1 <NA> 68.00
#> 1643 28111 37 1992 W 126436 1 <NA> 23.00
#> 1644 25 31 1992 W 126436 1 <NA> 12.00
#> 1645 85 59 1992 W 126436 1 <NA> 51.00
#> 1646 85 36 1992 W 126436 1 <NA> 138.00
#> 1647 71 22 1992 W 126436 1 <NA> 57.00
#> 1648 130 7 2008 W 126436 1 <NA> 11.00
#> 1649 28 34 2008 W 126436 1 <NA> 30.00
#> 1650 2 27 2008 W 126436 1 <NA> 532.00
#> 1651 81 48 2008 W 126436 1 <NA> 32.00
#> 1652 249 54 2008 W 126436 1 U 680.00
#> 1653 243 48 2008 W 126436 1 U 3128.00
#> 1654 26168 19 2008 T 164712 1 <NA> 1646.00
#> 1655 2 26 2008 W 126436 1 <NA> 1544.00
#> 1656 51 26 2008 T 164712 1 <NA> 562.00
#> 1657 <NA> 20 2006 W 126436 1 <NA> 24.00
#> 1658 25175 17 2006 W 126436 1 <NA> 506.00
#> 1659 33 12 2006 W 126436 1 <NA> 37.00
#> 1660 38 15 2006 W 126436 1 <NA> 1.00
#> 1661 74 44 2010 W 126436 1 <NA> 696.00
#> 1662 173 13 2010 W 126436 1 <NA> 260.00
#> 1663 210 23 2010 W 126436 1 <NA> 655.00
#> 1664 213 24 2010 W 126436 1 <NA> 2531.00
#> 1665 214 25 2010 W 126436 1 <NA> 928.00
#> 1666 60 18 2010 T 164712 1 <NA> 3134.00
#> 1667 60 23 2010 T 164712 1 <NA> 6475.00
#> 1668 118 5 2010 W 126436 1 <NA> 675.00
#> 1669 172 19 2010 W 126436 1 <NA> 964.00
#> 1670 67 35 2007 W 126436 1 <NA> 66.00
#> 1671 36 18 2007 W 126436 1 <NA> 402.00
#> 1672 185 1 2007 T 164712 1 U 6346.00
#> 1673 52 3 2007 T 164712 1 <NA> 972.00
#> 1674 52 14 2007 T 164712 1 <NA> 4366.00
#> 1675 283 41 2007 W 126436 1 <NA> 307.00
#> 1676 697 22 2007 W 126436 1 U 1500.00
#> 1677 25453 10 2007 T 164712 1 <NA> 764.00
#> 1678 41 44 2000 W 126436 1 <NA> 896.00
#> 1679 160 81 2000 W 126436 1 <NA> 764.00
#> 1680 30 15 2000 W 126436 1 <NA> 114.00
#> 1681 42 47 2000 W 126436 1 <NA> 716.00
#> 1682 <NA> 9 2000 W 126436 1 <NA> 1218.00
#> 1683 <NA> 40 2000 W 126436 1 <NA> 18.00
#> 1684 594 27 2000 W 126436 1 <NA> 842.00
#> 1685 611 42 2000 W 126436 1 <NA> 206.00
#> 1686 40 26 1991 W 126436 1 <NA> 254.00
#> 1687 50 32 1991 W 126436 1 <NA> 293.00
#> 1688 72 1 1991 W 126436 1 <NA> 142.00
#> 1689 76 41 1991 W 126436 1 <NA> 125.00
#> 1690 81 44 1991 W 126436 1 <NA> 164.00
#> 1691 83 46 1991 W 126436 1 <NA> 224.00
#> 1692 2602 43 1991 W 126436 1 <NA> 120.00
#> 1693 000001 11 1991 W 126436 1 <NA> 82.00
#> 1694 2604 44 1991 W 126436 1 <NA> 111.00
#> 1695 2605 45 1991 W 126436 1 <NA> 196.00
#> 1696 2412 80 1991 W 126436 1 <NA> 26.00
#> 1697 24 42 2012 W 126436 1 <NA> 1802.00
#> 1698 89 52 2012 W 126436 1 <NA> 449.00
#> 1699 28 9 2012 W 126436 1 <NA> 1346.00
#> 1700 31 21 1996 W 126436 1 <NA> 420.00
#> 1701 12 6 1996 W 126436 1 <NA> 261.00
#> 1702 75 83 1996 W 126436 1 <NA> 554.00
#> 1703 28 15 1996 W 126436 1 <NA> 274.00
#> 1704 30 16 1996 W 126436 1 <NA> 1965.00
#> 1705 51 29 1996 W 126436 1 <NA> 212.00
#> 1706 40 22 1996 W 126436 1 <NA> 9.00
#> 1707 93 44 1996 W 126436 1 <NA> 200.00
#> 1708 86 35 1996 W 126436 1 <NA> 718.00
#> 1709 78 27 1996 W 126436 1 <NA> 402.00
#> 1710 59 24 1995 W 126436 1 <NA> 165.00
#> 1711 45 45 1995 W 126436 1 <NA> 2079.00
#> 1712 71 67 1995 W 126436 1 <NA> 94.00
#> 1713 40 17 1995 W 126436 1 <NA> 280.00
#> 1714 <NA> 17 1995 W 126436 1 <NA> 1363.00
#> 1715 90 38 1995 W 126436 1 <NA> 4.00
#> 1716 <NA> 1 1995 W 126436 1 <NA> 414.00
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#> 1719 25 47 1995 T 164712 1 <NA> 828.00
#> 1720 257 12 1995 W 126436 1 <NA> 1800.00
#> 1721 250 5 1995 W 126436 1 <NA> 102.00
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#> 1724 01Jan 15 1997 T 164712 1 <NA> 152.00
#> 1725 01Jan 14 1997 T 164712 1 <NA> 48.00
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#> 1727 <NA> 36 1997 T 164712 1 <NA> 42.00
#> 1728 224 40 1997 W 126436 1 <NA> 1122.00
#> 1729 197 19 1997 W 126436 1 <NA> 132.00
#> 1730 756 26 1997 W 126436 1 <NA> 22.00
#> 1731 673 66 2001 T 164712 1 <NA> 418.00
#> 1732 6 3 2001 T 164712 1 <NA> 132.00
#> 1733 110 46 2001 T 164712 1 <NA> 205.00
#> 1734 <NA> 51 2001 T 164712 1 <NA> 126.00
#> 1735 206 3 2001 W 126436 1 <NA> 10.00
#> 1736 209 6 2001 W 126436 1 <NA> 876.00
#> 1737 251 42 2001 W 126436 1 <NA> 102.86
#> 1738 904 47 2001 T 164712 1 <NA> 1016.00
#> 1739 617 23 2001 T 164712 1 <NA> 550.00
#> 1740 233 41 2005 W 126436 1 U 574.00
#> 1741 33 33 2005 W 126436 1 <NA> 1598.00
#> 1742 <NA> 9 2005 T 164712 1 <NA> 100.00
#> 1743 <NA> 5 2005 T 164712 1 <NA> 516.00
#> 1744 <NA> 30 2005 T 164712 1 <NA> 110.00
#> 1745 68 33 2004 W 126436 1 <NA> 855.00
#> 1746 <NA> 10 2004 T 164712 1 <NA> 1826.00
#> 1747 <NA> 4 2004 T 164712 1 <NA> 144.00
#> 1748 22 8 2004 W 126436 1 <NA> 3068.00
#> 1749 2 2 2004 T 164712 1 <NA> 88.00
#> 1750 <NA> 26 2004 T 164712 1 <NA> 1082.00
#> 1751 220 23 2009 W 126436 1 <NA> 1173.00
#> 1752 24089 56 2009 T 164712 1 <NA> 163.00
#> 1753 24228 20 2009 T 164712 1 <NA> 169.00
#> 1754 116 2 2009 W 126436 1 <NA> 1636.00
#> 1755 24005 50 2009 T 164712 1 <NA> 39.00
#> 1756 57 5 2009 T 164712 1 <NA> 1346.00
#> 1757 57 37 2009 T 164712 1 <NA> 50.00
#> 1758 57 34 2009 T 164712 1 <NA> 780.00
#> 1759 244 31 2009 W 126436 1 U 1574.00
#> 1760 131 6 2009 W 126436 1 <NA> 246.00
#> 1761 137 9 2009 W 126436 1 <NA> 2575.00
#> 1762 24288 55 2009 T 164712 1 <NA> 1959.00
#> 1763 82 40 1993 W 126436 1 <NA> 140.00
#> 1764 7 4 1993 W 126436 1 <NA> 471.00
#> 1765 74 32 1993 W 126436 1 <NA> 40.00
#> 1766 63 15 1993 W 126436 1 <NA> 3.00
#> 1767 66 18 1993 W 126436 1 <NA> 107.00
#> 1768 264 33 1993 W 126436 1 <NA> 8191.00
#> 1769 55 27 2003 T 164712 1 <NA> 322.00
#> 1770 130 61 1998 T 164712 1 <NA> 493.00
#> 1771 36 17 1998 T 164712 1 <NA> 44.00
#> 1772 <NA> 34 1998 T 164712 1 <NA> 290.00
#> 1773 01Jan 48 1998 T 164712 1 <NA> 30.00
#> 1774 03Mar 63 1998 T 164712 1 <NA> 464.00
#> 1775 03Mar 64 1998 T 164712 1 <NA> 72.00
#> 1776 206 14 1998 T 164712 1 <NA> 194.00
#> 1777 217 22 1998 T 164712 1 <NA> 96.00
#> 1778 692 1 1998 T 164712 1 <NA> 4443.00
#> 1779 788 181 2002 T 164712 1 <NA> 100.00
#> 1780 194 19 2002 T 164712 1 <NA> 2544.00
#> 1781 <NA> 9 2002 T 164712 1 <NA> 1238.00
#> 1782 1278 37 2002 T 164712 1 <NA> 848.00
#> 1783 33 16 2002 T 164712 1 <NA> 974.00
#> 1784 24012 52 2002 T 164712 1 <NA> 1186.00
#> 1785 10 4 2002 T 164712 1 <NA> 1958.00
#> 1786 39 18 1999 T 164712 1 <NA> 140.00
#> 1787 <NA> 5 1999 T 164712 1 <NA> 94.00
#> 1788 02Feb 25 1999 T 164712 1 <NA> 64.00
#> 1789 246 52 1999 T 164712 1 <NA> 8.00
#> 1790 671 33 1999 T 164712 1 <NA> 1440.00
#> 1791 2 8 1999 T 164712 1 <NA> 1194.00
#> 1792 659 24 1999 T 164712 1 <NA> 364.00
#> 1793 23 13 1994 T 164712 1 <NA> 208.00
#> 1794 76 25 1994 W 126436 1 <NA> 88.00
#> 1795 74 39 1994 T 164712 1 <NA> 457.00
#> 1796 78 27 1994 W 126436 1 <NA> 350.00
#> 1797 60 9 1994 W 126436 1 <NA> 1022.00
#> 1798 83 32 1994 W 126436 1 <NA> 524.00
#> 1799 Mar 8 1994 T 164712 1 <NA> 88.00
#> 1800 61 10 1994 W 126436 1 <NA> 928.00
#> 1801 273 18 1994 W 126436 1 <NA> 170.00
#> 1802 283 28 1994 W 126436 1 <NA> 268.00
#> 1803 18 19 2011 W 126436 1 <NA> 930.00
#> 1804 187 21 2011 W 126436 1 <NA> 1869.00
#> 1805 24182 25 2011 W 126436 1 <NA> 1032.00
#> 1806 25394 15 2011 W 126436 1 U 8294.00
#> 1807 111 6 2008 W 126436 1 <NA> 20.00
#> 1808 30 35 2008 W 126436 1 <NA> 48.00
#> 1809 243 48 2008 W 126436 1 U 3128.00
#> 1810 24142 28 2008 T 164712 1 <NA> 324.00
#> 1811 132 7 2008 W 126436 1 <NA> 1243.00
#> 1812 51 28 2008 T 164712 1 <NA> 1696.00
#> 1813 51 33 2008 T 164712 1 <NA> 566.00
#> 1814 718 24 2008 W 126436 1 U 1312.00
#> 1815 2 29 2008 W 126436 1 <NA> 2040.00
#> 1816 51 27 2008 T 164712 1 <NA> 192.00
#> 1817 51 23 2008 T 164712 1 <NA> 3344.00
#> 1818 16 12 1992 W 126436 1 <NA> 11.00
#> 1819 81 56 1992 W 126436 1 <NA> 73.00
#> 1820 52 37 1992 W 126436 1 <NA> 124.00
#> 1821 86 60 1992 W 126436 1 <NA> 32.00
#> 1822 54 38 1992 W 126436 1 <NA> 97.00
#> 1823 22 15 1992 W 126436 1 <NA> 26.00
#> 1824 2504 46 1992 W 126436 1 <NA> 58.00
#> 1825 2518 16 1992 W 126436 1 <NA> 51.00
#> 1826 26012 41 1992 W 126436 1 <NA> 46.00
#> 1827 26021 29 1992 W 126436 1 <NA> 68.00
#> 1828 85 59 1992 W 126436 1 <NA> 51.00
#> 1829 56 7 1992 W 126436 1 <NA> 188.00
#> 1830 2 11 2006 W 126436 1 <NA> 706.00
#> 1831 49 26 2006 W 126436 1 <NA> 370.00
#> 1832 25193 8 2006 W 126436 1 <NA> 724.00
#> 1833 104 2 2006 W 126436 1 <NA> 35.00
#> 1834 81 38 2006 W 126436 1 <NA> 145.00
#> 1835 26104 3 2006 T 164712 1 <NA> 300.00
#> 1836 64 34 2007 W 126436 1 <NA> 703.00
#> 1837 24 12 2007 W 126436 1 <NA> 860.00
#> 1838 36 18 2007 W 126436 1 <NA> 402.00
#> 1839 283 41 2007 W 126436 1 <NA> 307.00
#> 1840 695 20 2007 W 126436 1 U 2134.00
#> 1841 102 2 2010 W 126436 1 <NA> 727.00
#> 1842 98 48 2010 W 126436 1 <NA> 646.00
#> 1843 207 20 2010 W 126436 1 <NA> 1955.00
#> 1844 213 24 2010 W 126436 1 <NA> 2531.00
#> 1845 60 18 2010 T 164712 1 <NA> 3134.00
#> 1846 60 23 2010 T 164712 1 <NA> 6475.00
#> 1847 78 48 2010 W 126436 1 <NA> 549.00
#> 1848 120 7 2010 W 126436 1 <NA> 794.00
#> 1849 172 19 2010 W 126436 1 <NA> 964.00
#> 1850 44 51 2000 W 126436 1 <NA> 558.00
#> 1851 243 40 2000 W 126436 1 <NA> 564.00
#> 1852 2 4 2000 T 164712 1 <NA> 12.00
#> 1853 89 52 2012 W 126436 1 <NA> 449.00
#> 1854 25193 36 2012 W 126436 1 U 64.00
#> 1855 112 2 2012 W 126436 1 <NA> 2507.00
#> 1856 24078 32 2012 W 126436 1 <NA> 765.00
#> 1857 19 14 1991 W 126436 1 <NA> 50.00
#> 1858 40 26 1991 W 126436 1 <NA> 254.00
#> 1859 49 31 1991 W 126436 1 <NA> 68.00
#> 1860 50 32 1991 W 126436 1 <NA> 293.00
#> 1861 55 35 1991 W 126436 1 <NA> 82.00
#> 1862 72 1 1991 W 126436 1 <NA> 142.00
#> 1863 76 41 1991 W 126436 1 <NA> 125.00
#> 1864 81 44 1991 W 126436 1 <NA> 164.00
#> 1865 2602 43 1991 W 126436 1 <NA> 120.00
#> 1866 2604 44 1991 W 126436 1 <NA> 111.00
#> 1867 2605 45 1991 W 126436 1 <NA> 196.00
#> 1868 26062 47 1991 W 126436 1 <NA> 81.00
#> 1869 26071 48 1991 W 126436 1 <NA> 213.00
#> 1870 25151 51 1991 W 126436 1 <NA> 121.00
#> 1871 000001 16 1991 W 126436 1 <NA> 260.00
#> 1872 25252 64 1991 W 126436 1 <NA> 11.00
#> 1873 25223 76 1991 W 126436 1 <NA> 106.00
#> 1874 25224 77 1991 W 126436 1 <NA> 136.00
#> 1875 2411 79 1991 W 126436 1 <NA> 1.00
#> 1876 000003 30 1991 W 126436 1 <NA> 92.00
#> 1877 01Jan 1 1991 W 126436 1 <NA> 142.00
#> 1878 000003 28 1991 W 126436 1 <NA> 119.00
#> 1879 03Mar 19 1991 W 126436 1 <NA> 192.00
#> 1880 03Mar 11 1991 W 126436 1 <NA> 80.00
#> 1881 000003 11 1991 W 126436 1 <NA> 67.00
#> 1882 000003 13 1991 W 126436 1 <NA> 84.00
#> 1883 000003 15 1991 W 126436 1 <NA> 90.00
#> 1884 22 12 1996 W 126436 1 <NA> 480.00
#> 1885 31 17 1996 W 126436 1 <NA> 91.00
#> 1886 57 31 1996 W 126436 1 <NA> 35.00
#> 1887 30 16 1996 W 126436 1 <NA> 1965.00
#> 1888 <NA> 34 1996 W 126436 1 <NA> 14.00
#> 1889 <NA> 17 1996 W 126436 1 <NA> 405.00
#> 1890 64 13 1996 W 126436 1 <NA> 384.00
#> 1891 100 49 1996 W 126436 1 <NA> 558.00
#> 1892 52 1 1996 W 126436 1 <NA> 2912.00
#> 1893 99 48 1996 W 126436 1 <NA> 704.00
#> 1894 78 27 1996 W 126436 1 <NA> 402.00
#> 1895 61 10 1996 W 126436 1 <NA> 858.00
#> 1896 78 46 2013 W 126436 1 <NA> 262.00
#> 1897 82 49 2013 W 126436 1 <NA> 266.00
#> 1898 134 49 1995 W 126436 1 <NA> 180.00
#> 1899 45 45 1995 W 126436 1 <NA> 2079.00
#> 1900 000001 23 1995 W 126436 1 <NA> 155.00
#> 1901 000001 10 1995 W 126436 1 <NA> 84.00
#> 1902 000001 21 1995 W 126436 1 <NA> 221.00
#> 1903 93 41 1995 W 126436 1 <NA> 136.00
#> 1904 94 42 1995 W 126436 1 <NA> 48.00
#> 1905 <NA> 7 1995 W 126436 1 <NA> 248.00
#> 1906 266 21 1995 W 126436 1 <NA> 726.00
#> 1907 265 20 1995 W 126436 1 <NA> 1026.00
#> 1908 257 12 1995 W 126436 1 <NA> 1800.00
#> 1909 250 5 1995 W 126436 1 <NA> 102.00
#> 1910 121 52 1997 T 164712 1 <NA> 458.00
#> 1911 29 29 1997 T 164712 1 <NA> 6.00
#> 1912 01Jan 13 1997 T 164712 1 <NA> 520.00
#> 1913 03Mar 64 1997 T 164712 1 <NA> 6.00
#> 1914 03Mar 23 1997 T 164712 1 <NA> 82.00
#> 1915 <NA> 36 1997 T 164712 1 <NA> 42.00
#> 1916 <NA> 16 1997 T 164712 1 <NA> 246.00
#> 1917 194 16 1997 W 126436 1 <NA> 608.00
#> 1918 195 17 1997 W 126436 1 <NA> 356.00
#> 1919 197 19 1997 W 126436 1 <NA> 132.00
#> 1920 2 16 1997 T 164712 1 <NA> 335.00
#> 1921 743 14 1997 W 126436 1 <NA> 526.00
#> 1922 745 16 1997 W 126436 1 <NA> 47.65
#> 1923 754 24 1997 W 126436 1 <NA> 418.00
#> CatIdentifier NoMeas SubFactor SubWgt CatCatchWgt LngtCode LngtClass
#> 1 1 17 1.0000 NA 13275 0 335
#> 2 1 17 1.0000 NA 13275 0 285
#> 3 1 17 1.0000 NA 13275 0 225
#> 4 1 17 1.0000 NA 13275 0 220
#> 5 1 17 1.0000 NA 13275 0 215
#> 6 1 17 1.0000 NA 13275 0 180
#> 7 1 17 1.0000 NA 13275 0 175
#> 8 1 17 1.0000 NA 13275 0 160
#> 9 1 17 1.0000 NA 13275 0 150
#> 10 1 17 1.0000 NA 13275 0 145
#> 11 1 17 1.0000 NA 13275 0 140
#> 12 1 93 1.0000 113900 113900 . 1360
#> 13 1 454 1.0000 NA 234500 1 127
#> 14 1 17 1.0000 NA 13275 0 130
#> 15 1 37 1.0000 NA 1033 1 127
#> 16 1 406 1.0000 257280 257280 . 1230
#> 17 1 273 1.0000 NA 484399 1 121
#> 18 1 163 1.0000 NA 2190 1 116
#> 19 1 255 1.0000 NA 158200 1 121
#> 20 1 141 1.0000 NA 2390 1 112
#> 21 1 775 1.0000 NA 5718 1 118
#> 22 1 29 1.0000 48300 48300 . 1170
#> 23 1 227 1.0000 NA 268580 1 118
#> 24 1 1958 1.0000 NA 1040200 1 118
#> 25 1 130 1.0000 NA 157570 1 116
#> 26 1 77 1.0000 NA 1540 1 110
#> 27 1 1545 1.0000 NA 1302400 1 117
#> 28 1 538 1.0000 NA 303000 1 116
#> 29 1 319 1.0000 NA 158200 1 115
#> 30 1 51 1.0000 NA 599 1 108
#> 31 1 78 1.0000 119000 119000 . 1130
#> 32 1 27 1.0000 NA 96200 1 113
#> 33 1 1368 1.0000 NA 607800 1 111
#> 34 1 742 1.0000 NA 267459 1 113
#> 35 1 10 1.0000 NA 76000 1 113
#> 36 1 128 1.0000 NA 1079 1 109
#> 37 1 197 1.0000 192900 192900 . 1120
#> 38 1 12 1.0000 NA 39544 1 118
#> 39 1 223 1.0000 149100 149100 . 1100
#> 40 1 864 1.0000 NA 247830 1 119
#> 41 1 68 1.0000 NA 2535 1 109
#> 42 1 77 1.0000 NA 1540 1 106
#> 43 1 457 1.0000 NA 42 1 112
#> 44 1 63 1.0000 NA 48400 1 111
#> 45 1 130 1.0000 NA 2374 1 111
#> 46 1 764 1.0000 139400 139400 . 1150
#> 47 1 85 1.0000 NA 46000 1 107
#> 48 1 132 1.0000 NA 61000 1 111
#> 49 1 49 1.0000 NA 1013 1 104
#> 50 1 277 1.0000 NA 1297 1 106
#> 51 1 22 1.0000 NA 219 1 106
#> 52 1 1499 1.0000 NA 5688600 1 106
#> 53 1 848 1.0000 NA 968860 1 116
#> 54 1 390 1.0000 NA 16278 1 109
#> 55 1 151 1.0000 NA 2962 1 109
#> 56 1 972 1.0000 322476 322476 . 1130
#> 57 1 164 1.0000 NA 3531 1 103
#> 58 1 180 1.0000 NA 46605 1 109
#> 59 1 97 1.0000 NA 3360 1 108
#> 60 1 32 1.0000 47100 47100 . 1060
#> 61 1 552 1.0000 419300 419300 . 1130
#> 62 1 85 1.0000 NA 37470 1 108
#> 63 1 43 1.0000 67365 67365 . 1070
#> 64 1 468 1.0000 NA 597000 1 107
#> 65 1 235 1.0000 NA 98500 1 110
#> 66 1 1332 1.0000 NA 574000 1 104
#> 67 1 508 1.0000 NA 268000 1 107
#> 68 1 231 1.0000 204000 204000 . 1050
#> 69 1 283 1.0000 NA 369740 1 112
#> 70 1 325 1.0000 NA 253940 1 111
#> 71 1 68 1.0000 NA 2535 1 104
#> 72 1 214 1.0000 NA 326000 1 107
#> 73 1 1462 1.0000 NA 1872800 1 107
#> 74 1 421 1.0000 NA 382800 1 107
#> 75 1 143 1.0000 NA 185600 1 109
#> 76 1 291 1.0000 NA 9063 1 106
#> 77 1 80 1.0000 66500 66500 . 1040
#> 78 1 382 1.0000 NA 10120 1 106
#> 79 1 212 1.0000 324500 324500 . 1050
#> 80 1 124 1.0000 NA 419000 1 105
#> 81 1 565 1.0000 216000 432000 1 110
#> 82 1 75 1.0000 NA 108824 1 105
#> 83 1 11 1.0000 NA 74600 1 105
#> 84 1 41 1.0000 NA 1500 1 100
#> 85 1 413 1.0000 NA 5844000 1 110
#> 86 1 493 1.0000 NA 577785 1 105
#> 87 1 233 1.0000 NA 4381 1 103
#> 88 1 40 1.0000 NA 761 1 105
#> 89 1 24 1.0000 NA 28400 1 105
#> 90 1 110 1.0000 108900 108900 . 1040
#> 91 1 47 1.0000 NA 1155 1 104
#> 92 1 293 1.0000 NA 2710 1 101
#> 93 1 139 1.0000 NA 1266 1 105
#> 94 1 943 1.0000 430200 430200 . 1080
#> 95 2 234 1.0000 121600 121600 . 1090
#> 96 1 97 1.0000 NA 137200 1 105
#> 97 1 4 1.0000 NA 151 1 101
#> 98 1 639 1.0000 NA 1289466 1 108
#> 99 1 710 1.0000 323900 323900 . 1080
#> 100 1 165 1.0000 NA 5280 1 103
#> 101 1 204 1.0000 NA 562000 1 103
#> 102 1 52 1.0000 NA 140000 1 103
#> 103 1 164 1.0000 NA 3531 1 98
#> 104 1 77 1.0000 NA 1540 1 98
#> 105 1 109 1.0000 NA 219200 1 103
#> 106 1 511 1.0000 NA 744000 1 103
#> 107 1 97 1.0000 NA 225199 1 103
#> 108 1 248 1.0000 NA 212000 1 101
#> 109 1 321 1.0000 NA 202586 1 108
#> 110 1 58 1.0000 NA 868 1 104
#> 111 1 481 1.0000 NA 666500 1 109
#> 112 1 848 1.0000 NA 968860 1 109
#> 113 1 281 1.0000 NA 421630 1 109
#> 114 1 198 1.0000 NA 1660 1 103
#> 115 1 15 1.0000 NA 415 1 100
#> 116 1 188 1.0000 NA 226300 1 100
#> 117 1 227 1.0000 NA 268580 1 103
#> 118 1 103 1.0000 51880 51880 . 1020
#> 119 1 29 1.0000 NA 800 1 102
#> 120 1 178 1.0000 NA 208399 1 102
#> 121 1 54 1.0000 NA 100700 1 102
#> 122 1 54 1.0000 NA 116300 1 97
#> 123 1 539 1.0000 181300 181300 . 1060
#> 124 1 79 1.0000 NA 116780 1 107
#> 125 1 2 1.0000 NA 1 1 102
#> 126 1 68 1.0000 NA 2535 1 99
#> 127 1 188 1.0000 NA 226300 1 99
#> 128 1 393 1.0000 NA 4846 1 102
#> 129 1 45 1.0000 NA 31205 1 102
#> 130 2 260 1.0000 NA 219700 1 104
#> 131 1 1965 1.0000 1978100 1978100 . 1010
#> 132 1 646 1.0000 409300 409300 . 1060
#> 133 1 2531 1.0000 1547900 1547900 . 1060
#> 134 1 442 1.0000 NA 1600 1 101
#> 135 1 389 1.0000 NA 209600 1 101
#> 136 1 196 1.0000 NA 4070 1 96
#> 137 1 179 1.0000 NA 2400 1 96
#> 138 1 100 1.0000 NA 72000 1 102
#> 139 1 20 1.0000 NA 42000 1 98
#> 140 1 180 1.0000 194500 194500 . 990
#> 141 1 137 1.0000 NA 381800 1 99
#> 142 1 277 1.0000 NA 92700 1 102
#> 143 1 1198 1.0000 NA 2912 1 103
#> 144 1 404 1.0000 NA 5074 1 101
#> 145 1 136 1.0000 NA 135800 1 101
#> 146 1 384 1.0000 NA 261000 1 101
#> 147 1 48 1.0000 NA 701 1 98
#> 148 1 558 1.0000 270500 270500 . 1050
#> 149 1 36 1.0000 60300 60300 . 1000
#> 150 1 13 1.0000 NA 524 1 100
#> 151 1 8 1.0000 NA 29131 1 100
#> 152 1 234 1.0000 NA 182000 1 100
#> 153 1 27 1.0000 NA 117353 1 100
#> 154 1 145 1.0000 NA 2724 1 100
#> 155 1 232 1.0000 NA 763200 1 100
#> 156 1 291 1.0000 NA 9063 1 100
#> 157 1 4 1.0000 NA 25884 1 100
#> 158 1 379 1.0000 NA 161240 1 100
#> 159 1 673 1.0000 500400 500400 . 1040
#> 160 1 76 1.0000 NA 1260 1 100
#> 161 1 137 1.0000 NA 68400 1 100
#> 162 1 142 1.0000 NA 3942 1 95
#> 163 1 17 1.0000 NA 42600 1 95
#> 164 1 30 1.0000 NA 170 1 98
#> 165 1 24 1.0000 NA 73900 1 98
#> 166 1 371 1.0000 NA 135440 1 101
#> 167 1 130 1.0000 NA 2374 1 100
#> 168 1 134 1.0000 NA 609000 1 100
#> 169 1 345 1.0000 NA 248750 1 102
#> 170 1 24 1.0000 NA 17105 1 100
#> 171 1 150 1.0000 NA 123660 1 100
#> 172 1 2531 1.0000 1547900 1547900 . 1040
#> 173 2 397 2.7646 NA 536900 1 104
#> 174 1 5 1.0000 NA 150 1 97
#> 175 1 25 1.0000 NA 142000 1 99
#> 176 1 209 1.0000 NA 599200 1 99
#> 177 1 597 1.0000 NA 758000 1 99
#> 178 1 27 1.0000 39925 39925 . 970
#> 179 1 10 1.0000 NA 45400 1 97
#> 180 1 13 1.0000 NA 472 1 97
#> 181 1 51 1.0000 NA 198200 1 97
#> 182 1 41 1.0000 NA 607 1 94
#> 183 1 213 1.0000 NA 2960 1 94
#> 184 1 NA 1.0000 NA 10140 1 96
#> 185 1 378 1.0000 NA 140100 1 96
#> 186 1 107 1.0000 NA 92432 1 100
#> 187 1 420 1.0000 NA 324500 1 100
#> 188 1 175 1.0000 NA 234000 1 99
#> 189 1 1252 1.0000 NA 819336 1 103
#> 190 1 42 1.0000 NA 40445 1 99
#> 191 1 538 1.0000 NA 303000 1 99
#> 192 1 1610 1.0000 678200 678200 . 980
#> 193 1 225 1.0000 207845 207845 . 980
#> 194 1 129 1.0000 NA 765 1 96
#> 195 1 68 1.0000 NA 2535 1 96
#> 196 1 34 1.0000 NA 80000 1 96
#> 197 1 8 1.0000 NA 29131 1 98
#> 198 1 558 1.0000 NA 579000 1 98
#> 199 1 234 1.0000 NA 182000 1 98
#> 200 1 248 1.0000 NA 93400 1 102
#> 201 1 178 1.0000 95500 95500 . 1020
#> 202 1 717 1.0000 397200 397200 . 1020
#> 203 1 493 1.0000 NA 577785 1 98
#> 204 1 113 1.0000 NA 63200 1 98
#> 205 1 3 1.0000 NA 23399 1 98
#> 206 1 395 1.0000 NA 310019 1 98
#> 207 1 104 1.0000 NA 201940 1 98
#> 208 1 54 1.0000 NA 47245 1 98
#> 209 1 49 1.0000 NA 24300 1 98
#> 210 1 155 1.0000 NA 1570 1 96
#> 211 1 29 1.0000 26900 26900 . 960
#> 212 1 164 1.0000 NA 3531 1 93
#> 213 1 41 1.0000 NA 593 1 93
#> 214 1 213 1.0000 NA 2960 1 93
#> 215 1 89 1.0000 NA 70000 1 99
#> 216 1 710 1.0000 323900 323900 . 1020
#> 217 1 81 1.0000 NA 708 1 99
#> 218 1 752 1.0000 NA 3761 1 98
#> 219 1 552 1.0000 419300 419300 . 1020
#> 220 1 727 1.0000 502400 502400 . 1020
#> 221 1 520 1.0000 341600 341600 . 1020
#> 222 1 2531 1.0000 1547900 1547900 . 1020
#> 223 1 945 1.0000 804400 804400 . 1020
#> 224 1 232 1.0000 NA 57400 1 100
#> 225 1 14 1.0000 NA 33938 1 100
#> 226 1 250 1.0000 NA 2600 1 98
#> 227 1 51 1.0000 NA 77380 1 98
#> 228 1 201 1.0000 NA 769400 1 97
#> 229 1 366 1.0000 NA 334140 1 102
#> 230 1 545 1.0000 295136 295136 . 1010
#> 231 1 178 1.0000 95500 95500 . 1010
#> 232 1 370 1.0000 147600 147600 . 1030
#> 233 1 612 1.0000 NA 2470000 1 103
#> 234 1 548 1.0000 NA 560200 1 97
#> 235 1 1 1.0000 NA 8290 1 97
#> 236 1 108 1.0000 NA 129866 1 97
#> 237 1 230 1.0000 NA 178400 1 97
#> 238 1 532 1.0000 NA 442086 1 101
#> 239 1 639 1.0000 NA 1289466 1 101
#> 240 1 297 1.0000 189700 189700 . 1010
#> 241 1 NA 1.0000 NA 2700 1 95
#> 242 1 12 1.0000 NA 265 1 95
#> 243 1 448 1.0000 NA 246600 1 98
#> 244 1 245 1.0000 NA 114180 1 98
#> 245 1 482 1.0000 NA 140100 1 98
#> 246 1 1332 1.0000 NA 574000 1 94
#> 247 1 378 1.0000 NA 250000 1 94
#> 248 1 1104 1.0000 NA 1129000 1 97
#> 249 1 652 1.0000 NA 277000 1 97
#> 250 1 138 1.0000 NA 1182 1 92
#> 251 1 114 1.0000 NA 92880 1 97
#> 252 1 60 1.0000 NA 860 1 97
#> 253 1 466 1.0000 NA 184370 1 97
#> 254 1 129 1.0000 NA 55400 1 101
#> 255 1 215 1.0000 178900 178900 . 960
#> 256 1 162 1.0000 NA 8834 1 96
#> 257 1 273 1.0000 NA 705600 1 96
#> 258 1 12 1.0000 NA 26860 1 96
#> 259 1 314 1.0000 NA 321000 1 96
#> 260 1 445 1.0000 NA 453040 1 102
#> 261 1 1243 1.0000 314690 314690 . 1020
#> 262 1 823 1.0000 NA 766200 1 102
#> 263 1 54 1.0000 NA 68900 1 94
#> 264 1 900 1.0000 NA 453600 1 100
#> 265 1 315 1.0000 NA 508600 1 100
#> 266 1 161 1.0000 NA 175420 1 100
#> 267 1 61 1.0000 NA 55397 1 96
#> 268 1 144 1.0000 NA 1400 1 96
#> 269 1 10 1.0000 NA 76000 1 96
#> 270 1 71 1.0000 NA 33600 1 96
#> 271 1 2 1.0000 NA 12610 1 96
#> 272 1 73 1.0000 NA 720 1 96
#> 273 1 955 1.0000 NA 5830 1 96
#> 274 1 238 1.0000 NA 139000 1 96
#> 275 1 785 1.0000 513900 1668240 1 100
#> 276 1 3 1.0000 NA 25400 1 97
#> 277 1 128 1.0000 NA 85200 1 97
#> 278 1 107 1.0000 NA 92432 1 97
#> 279 1 28 1.0000 NA 34400 1 97
#> 280 1 92 1.0000 NA 44 1 97
#> 281 1 67 1.0000 72000 72000 . 940
#> 282 1 184 1.0000 NA 2552 1 94
#> 283 1 350 1.0000 NA 827200 1 94
#> 284 1 457 1.0000 NA 42 1 96
#> 285 1 106 1.0000 NA 4560 1 93
#> 286 1 6 1.0000 NA 22600 1 93
#> 287 1 125 1.0000 NA 3523 1 91
#> 288 1 96 1.0000 NA 317000 1 91
#> 289 2 395 1.0000 NA 403160 1 98
#> 290 1 581 1.0000 NA 361200 1 100
#> 291 1 52 1.0000 NA 140000 1 95
#> 292 1 331 1.0000 NA 958320 1 99
#> 293 1 292 1.0000 193300 193300 . 990
#> 294 1 616 1.0000 148600 148600 . 990
#> 295 1 76 1.0000 NA 196400 1 95
#> 296 1 62 1.0000 NA 35650 1 95
#> 297 1 4 1.0000 NA 39600 1 95
#> 298 1 485 1.0000 NA 482000 1 95
#> 299 1 188 1.0000 NA 226300 1 93
#> 300 1 97 1.0000 NA 225199 1 95
#> 301 1 425 1.0000 NA 223000 1 95
#> 302 1 108 1.0000 NA 129866 1 95
#> 303 1 72 1.0000 NA 55350 1 96
#> 304 1 520 1.0000 NA 750000 1 96
#> 305 1 995 1.0000 NA 840800 1 96
#> 306 1 511 1.0000 NA 1179400 1 95
#> 307 1 134 1.0000 NA 609000 1 95
#> 308 1 1110 1.0000 NA 982000 1 93
#> 309 1 283 1.0000 NA 369740 1 99
#> 310 1 1332 1.0000 NA 574000 1 92
#> 311 1 633 1.0000 NA 120000 1 92
#> 312 1 399 1.0000 NA 135199 1 92
#> 313 1 378 1.0000 NA 250000 1 92
#> 314 1 143 1.0000 NA 185600 1 97
#> 315 1 385 1.0000 NA 1750 1 97
#> 316 1 224 1.0000 NA 2201 1 90
#> 317 1 120 1.0000 NA 2340 1 90
#> 318 1 111 1.0000 NA 2800 1 90
#> 319 1 400 1.0000 NA 3280 1 95
#> 320 1 114 1.0000 NA 92880 1 95
#> 321 1 319 1.0000 NA 158200 1 95
#> 322 2 16 1.0000 30820 30820 . 1000
#> 323 1 612 1.0000 NA 2470000 1 100
#> 324 1 211 1.0000 NA 5160 1 94
#> 325 1 88 1.0000 NA 102000 1 94
#> 326 1 19 1.0000 NA 29740 1 94
#> 327 1 33 1.0000 NA 64800 1 94
#> 328 1 11 1.0000 NA 74600 1 94
#> 329 1 2 1.0000 NA 7900 1 92
#> 330 1 6 1.0000 NA 17055 1 94
#> 331 1 108 1.0000 NA 38600 1 95
#> 332 1 597 1.0000 NA 758000 1 94
#> 333 1 710 1.0000 323900 323900 . 980
#> 334 1 482 1.0000 NA 140100 1 95
#> 335 1 2538 1.0000 NA 2561680 1 95
#> 336 1 2531 1.0000 1547900 1547900 . 980
#> 337 1 44 1.0000 NA 70000 1 94
#> 338 1 1480 1.0000 NA 1486200 1 94
#> 339 1 155 1.0000 NA 1570 1 92
#> 340 1 136 1.0000 NA 95600 1 92
#> 341 1 1332 1.0000 NA 574000 1 91
#> 342 1 633 1.0000 NA 120000 1 91
#> 343 1 409 1.0000 NA 374000 1 91
#> 344 1 848 1.0000 NA 968860 1 99
#> 345 1 819 1.0000 NA 888280 1 99
#> 346 1 23 1.0000 NA 18650 1 94
#> 347 1 318 1.0000 NA 163840 1 94
#> 348 1 371 1.0000 NA 296000 1 94
#> 349 1 164 1.0000 NA 3531 1 89
#> 350 1 87 1.0000 NA 750 1 89
#> 351 1 2212 1.0000 279500 279500 . 970
#> 352 1 444 1.0000 131330 131330 . 970
#> 353 1 1551 1.0000 549400 549400 . 970
#> 354 1 246 1.0000 311200 311200 . 970
#> 355 1 210 1.0000 156900 1355560 1 97
#> 356 1 311 1.0000 234980 234980 . 930
#> 357 1 35 1.0000 99030 99030 . 930
#> 358 1 661 1.0000 729000 729000 . 930
#> 359 1 544 1.0000 NA 1319800 1 93
#> 360 1 9 1.0000 NA 352 1 93
#> 361 1 481 1.0000 NA 167000 1 93
#> 362 1 10 1.0000 NA 20700 1 93
#> 363 1 61 1.0000 NA 55397 1 93
#> 364 1 145 1.0000 NA 2724 1 93
#> 365 1 593 1.0000 NA 361000 1 93
#> 366 1 24 1.0000 NA 34800 1 93
#> 367 1 97 1.0000 NA 225199 1 93
#> 368 1 219 1.0000 NA 3726 1 93
#> 369 1 18 1.0000 NA 24000 1 93
#> 370 1 125 1.0000 NA 53000 1 94
#> 371 1 100 1.0000 NA 72000 1 94
#> 372 1 368 1.0000 NA 72500 1 94
#> 373 1 720 1.0000 NA 509920 1 93
#> 374 1 508 1.0000 NA 879799 1 93
#> 375 1 384 1.0000 NA 201720 1 94
#> 376 1 5047 1.7130 1777000 3044001 . 970
#> 377 1 617 1.0000 NA 436200 1 94
#> 378 1 457 1.0000 NA 42 1 93
#> 379 1 793 1.0000 NA 997600 1 93
#> 380 1 39 1.0000 NA 76000 1 95
#> 381 1 256 1.0000 NA 88750 1 97
#> 382 1 307 1.0000 355358 355358 . 970
#> 383 1 258 1.0000 NA 8106 1 91
#> 384 1 350 1.0000 NA 827200 1 91
#> 385 1 600 1.0000 NA 2270 1 90
#> 386 1 247 1.0000 NA 1405 1 90
#> 387 1 379 1.0000 NA 158000 1 90
#> 388 1 81 1.0000 NA 68000 1 90
#> 389 1 378 1.0000 NA 250000 1 90
#> 390 1 1177 1.0000 596200 596200 . 970
#> 391 1 68 1.0000 NA 28045 1 93
#> 392 1 114 1.0000 NA 92880 1 93
#> 393 1 1 1.0000 NA 155 1 93
#> 394 1 55 1.0000 NA 132320 1 96
#> 395 1 673 1.0000 500400 500400 . 960
#> 396 1 1228 1.0000 844270 844270 . 960
#> 397 1 595 1.0000 NA 109460 1 96
#> 398 1 1224 1.0000 409500 409500 . 960
#> 399 1 469 1.0000 307980 1063220 1 96
#> 400 1 616 1.0000 NA 969600 1 92
#> 401 1 108 1.0000 NA 1310 1 88
#> 402 1 41 1.0000 NA 1500 1 88
#> 403 1 141 1.0000 NA 2390 1 88
#> 404 1 17 1.0000 NA 25400 1 88
#> 405 1 59 1.0000 NA 109155 1 92
#> 406 1 33 1.0000 NA 51000 1 92
#> 407 1 50 1.0000 NA 1984 1 92
#> 408 1 335 1.0000 NA 378300 1 92
#> 409 1 338 1.0000 NA 640000 1 90
#> 410 1 376 1.0000 235700 235700 . 960
#> 411 1 202 1.0000 NA 130800 1 92
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#> 413 1 493 1.0000 NA 577785 1 92
#> 414 1 39 1.0000 NA 57799 1 92
#> 415 1 59 1.0000 NA 72200 1 92
#> 416 1 105 1.0000 NA 199800 1 92
#> 417 1 10 1.0000 NA 30559 1 92
#> 418 1 468 1.0000 NA 1063000 1 96
#> 419 1 549 1.0000 409900 409900 . 960
#> 420 1 43 1.0000 NA 53500 1 93
#> 421 1 371 1.0000 NA 135440 1 93
#> 422 1 984 1.0000 NA 602799 1 93
#> 423 1 658 1.0000 NA 363903 1 93
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#> 427 1 981 1.0000 325200 325200 . 960
#> 428 1 1330 1.0000 469414 469414 . 960
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#> 430 1 166 1.0000 NA 339080 1 97
#> 431 1 96 1.0000 NA 178264 1 97
#> 432 1 612 1.0000 NA 2470000 1 97
#> 433 1 184 1.0000 NA 2552 1 90
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#> 435 1 47 1.0000 NA 86600 1 90
#> 436 2 463 1.7171 NA 229210 1 98
#> 437 1 1332 1.0000 NA 574000 1 89
#> 438 1 745 1.0000 229300 229300 . 950
#> 439 1 1453 1.0000 NA 2906 1 95
#> 440 1 773 1.0000 254700 254700 . 950
#> 441 1 55 1.0000 NA 132320 1 95
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#> 445 1 466 1.0000 NA 184370 1 92
#> 446 1 103 1.0000 NA 85500 1 92
#> 447 1 44 1.0000 58335 58335 . 910
#> 448 1 78 1.0000 119000 119000 . 910
#> 449 1 118 1.0000 174600 174600 . 910
#> 450 1 49 1.0000 NA 1433 1 91
#> 451 1 418 1.0000 NA 811000 1 91
#> 452 1 352 1.0000 NA 253800 1 91
#> 453 1 142 1.0000 NA 3942 1 87
#> 454 1 40 1.0000 NA 612 1 87
#> 455 1 22 1.0000 NA 601 1 87
#> 456 1 164 1.0000 NA 3531 1 87
#> 457 1 38 1.0000 NA 533 1 87
#> 458 1 129 1.0000 NA 2040 1 87
#> 459 1 213 1.0000 NA 2960 1 87
#> 460 1 173 1.0000 NA 1860 1 87
#> 461 1 196 1.0000 NA 135629 1 91
#> 462 1 185 1.0000 NA 156310 1 91
#> 463 1 52 1.0000 NA 143700 1 91
#> 464 1 157 1.0000 NA 112080 1 91
#> 465 1 7 1.0000 NA 25600 1 91
#> 466 1 209 1.0000 NA 599200 1 91
#> 467 1 2964 1.0000 1155800 1155800 . 950
#> 468 1 37 1.0000 NA 355 1 89
#> 469 1 11 1.0000 NA 332 1 89
#> 470 1 62 1.0000 NA 25500 1 91
#> 471 1 26 1.0000 NA 36600 1 91
#> 472 1 493 1.0000 NA 577785 1 91
#> 473 1 17 1.0000 NA 372 1 91
#> 474 1 26 1.0000 NA 59600 1 91
#> 475 1 390 1.0000 NA 16278 1 91
#> 476 1 291 1.0000 NA 9063 1 91
#> 477 1 12 1.0000 NA 42000 1 91
#> 478 2 500 2.3998 NA 529740 1 95
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#> 480 1 255 1.0000 NA 158200 1 92
#> 481 1 371 1.0000 NA 135440 1 92
#> 482 1 8 1.0000 NA 12050 1 92
#> 483 1 390 1.0000 NA 329400 1 92
#> 484 1 384 1.0000 NA 201720 1 92
#> 485 1 334 1.0000 NA 542800 1 92
#> 486 1 1229 1.0000 NA 539006 1 92
#> 487 1 395 1.0000 NA 363200 1 92
#> 488 1 439 1.0000 NA 990400 1 92
#> 489 1 307 1.0000 355358 355358 . 950
#> 490 1 567 1.0000 278500 278500 . 950
#> 491 1 10 1.0000 NA 39014 1 95
#> 492 1 289 1.0000 219800 219800 . 950
#> 493 1 147 1.0000 NA 12 1 91
#> 494 1 36 1.0000 NA 779 1 91
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#> 1467 1 112 1.0000 NA 195964 1 84
#> 1468 1 2698 1.0000 1191500 1191500 . 840
#> 1469 1 246 1.0000 311200 311200 . 840
#> 1470 1 2575 1.0000 1652600 1652600 . 840
#> 1471 1 558 1.0000 357200 357200 . 840
#> 1472 1 265 1.0000 NA 157700 1 82
#> 1473 1 89 1.0000 NA 70000 1 82
#> 1474 1 414 1.0000 NA 588000 1 82
#> 1475 1 34 1.0000 NA 33 1 82
#> 1476 1 42 1.0000 NA 20300 1 81
#> 1477 1 258 1.0000 NA 135200 1 81
#> 1478 1 30 1.0000 NA 3 1 81
#> 1479 1 415 1.0000 NA 278000 1 81
#> 1480 1 457 1.0000 NA 42 1 81
#> 1481 1 262 1.0000 NA 449400 1 81
#> 1482 1 134 1.0000 NA 609000 1 81
#> 1483 1 116 1.0000 NA 887 1 79
#> 1484 1 26 1.0000 NA 545 1 79
#> 1485 1 37 1.0000 NA 355 1 79
#> 1486 1 68 1.0000 NA 2535 1 79
#> 1487 1 15 1.0000 NA 415 1 79
#> 1488 1 127 1.0000 NA 90879 1 79
#> 1489 1 57 1.0000 NA 146199 1 79
#> 1490 1 149 1.0000 NA 75000 1 79
#> 1491 1 54 1.0000 NA 68900 1 79
#> 1492 1 188 1.0000 NA 226300 1 79
#> 1493 1 2964 1.0000 1155800 1155800 . 840
#> 1494 1 583 1.0000 NA 231800 1 84
#> 1495 1 785 1.0000 513900 1668240 1 84
#> 1496 1 630 1.0000 309200 618400 1 84
#> 1497 1 625 1.0000 334400 334400 . 840
#> 1498 1 625 1.0000 248500 248500 . 860
#> 1499 1 455 1.0000 NA 129420 1 85
#> 1500 1 864 1.0000 NA 247830 1 85
#> 1501 2 48 1.0000 89700 89700 . 850
#> 1502 1 142 1.0000 NA 179740 1 85
#> 1503 1 1564 1.0000 NA 1051800 1 85
#> 1504 1 848 1.0000 NA 968860 1 85
#> 1505 1 819 1.0000 NA 888280 1 85
#> 1506 1 823 1.0000 NA 766200 1 85
#> 1507 1 41 1.0000 NA 607 1 77
#> 1508 1 293 1.0000 NA 3352 1 77
#> 1509 1 54 1.0000 NA 673 1 77
#> 1510 1 142 1.0000 NA 3942 1 77
#> 1511 1 125 1.0000 NA 3523 1 77
#> 1512 1 111 1.0000 NA 2800 1 77
#> 1513 1 196 1.0000 NA 4070 1 77
#> 1514 1 62 1.0000 NA 806 1 77
#> 1515 1 35 1.0000 NA 710 1 77
#> 1516 1 35 1.0000 NA 81400 1 77
#> 1517 1 844 1.0000 NA 545080 1 81
#> 1518 1 552 1.0000 419300 419300 . 840
#> 1519 1 696 1.0000 366200 366200 . 840
#> 1520 1 2531 1.0000 1547900 1547900 . 840
#> 1521 1 928 1.0000 584600 584600 . 840
#> 1522 1 945 1.0000 804400 804400 . 840
#> 1523 1 467 1.0000 NA 1845600 1 84
#> 1524 1 202 1.0000 168560 628520 1 84
#> 1525 1 594 1.0000 NA 6467880 1 84
#> 1526 1 549 1.0000 409900 409900 . 840
#> 1527 1 675 1.0000 494400 494400 . 840
#> 1528 1 1602 1.0000 705500 705500 . 840
#> 1529 1 558 1.0000 270500 270500 . 840
#> 1530 1 1062 1.0000 340700 340700 . 840
#> 1531 1 562 1.0000 NA 777824 1 84
#> 1532 1 656 1.0000 NA 241000 1 84
#> 1533 1 576 1.0000 NA 596200 1 84
#> 1534 1 1940 1.0000 518100 518100 . 840
#> 1535 1 6 1.0000 NA 10500 1 84
#> 1536 1 394 1.0000 NA 493646 1 84
#> 1537 1 307 1.0000 355358 355358 . 840
#> 1538 1 981 1.0000 325200 325200 . 840
#> 1539 1 750 1.0000 NA 524400 1 84
#> 1540 1 1610 1.0000 678200 678200 . 800
#> 1541 1 110 1.0000 108900 108900 . 800
#> 1542 1 51 1.0000 NA 1060 1 80
#> 1543 1 93 1.0000 113900 113900 . 800
#> 1544 1 35 1.0000 99030 99030 . 800
#> 1545 1 100 1.0000 NA 2660 1 80
#> 1546 1 133 1.0000 NA 3301 1 80
#> 1547 1 33 1.0000 NA 460 1 80
#> 1548 1 124 1.0000 NA 419000 1 80
#> 1549 1 107 1.0000 NA 329700 1 80
#> 1550 1 201 1.0000 NA 244600 1 80
#> 1551 1 199 1.0000 NA 409800 1 80
#> 1552 1 198 1.0000 NA 362000 1 80
#> 1553 1 92 1.0000 87065 87065 . 790
#> 1554 1 241 1.0000 NA 16680 1 79
#> 1555 1 240 1.0000 192375 192375 . 790
#> 1556 1 280 1.0000 145200 145200 . 790
#> 1557 1 45 1.0000 NA 698 1 79
#> 1558 1 184 1.0000 NA 2552 1 79
#> 1559 1 248 1.0000 NA 212000 1 79
#> 1560 1 618 1.0000 NA 541600 1 79
#> 1561 1 449 1.0000 255400 255400 . 840
#> 1562 1 301 1.0000 175300 175300 . 840
#> 1563 1 509 1.0000 224540 2216820 1 84
#> 1564 1 62 1.0000 NA 37900 1 80
#> 1565 1 60 1.0000 NA 36605 1 80
#> 1566 1 5 1.0000 NA 12400 1 80
#> 1567 1 10 1.0000 NA 22800 1 80
#> 1568 1 67 1.0000 NA 58400 1 80
#> 1569 1 561 1.0000 NA 1282400 1 80
#> 1570 1 304 1.0000 NA 561800 1 80
#> 1571 1 559 1.0000 NA 857800 1 80
#> 1572 1 146 1.0000 NA 127500 1 80
#> 1573 1 1666 1.0000 278100 278100 . 840
#> 1574 1 279 1.0000 110160 646120 1 84
#> 1575 1 37 1.0000 NA 524 1 81
#> 1576 1 130 1.0000 NA 48800 1 81
#> 1577 1 18 1.0000 NA 19100 1 81
#> 1578 1 123 1.0000 NA 48000 1 81
#> 1579 1 435 1.0000 NA 227000 1 81
#> 1580 1 20 1.0000 NA 27600 1 81
#> 1581 1 522 1.0000 97666 97666 . 820
#> 1582 1 538 1.0000 110388 110388 . 820
#> 1583 1 97 1.0000 NA 1500 1 82
#> 1584 1 186 1.0000 NA 40500 1 82
#> 1585 1 135 1.0000 NA 128670 1 82
#> 1586 1 414 1.0000 187400 187400 . 820
#> 1587 1 202 1.0000 NA 150600 1 83
#> 1588 1 315 1.0000 NA 508600 1 83
#> 1589 1 379 1.0000 NA 228880 1 83
#> 1590 1 105 1.0000 NA 1280 1 78
#> 1591 1 140 1.0000 NA 1020 1 78
#> 1592 1 108 1.0000 NA 145300 1 78
#> 1593 1 378 1.0000 NA 250000 1 78
#> 1594 1 454 1.0000 NA 234500 1 78
#> 1595 1 54 1.0000 NA 101000 1 78
#> 1596 1 782 1.0000 503638 503638 . 830
#> 1597 1 331 1.0000 NA 958320 1 83
#> 1598 1 826 1.0000 560410 560410 . 830
#> 1599 1 458 1.0000 NA 413162 1 83
#> 1600 1 432 1.0000 NA 2009460 1 83
#> 1601 1 6 1.0000 NA 21354 1 83
#> 1602 1 226 1.0000 NA 286266 1 83
#> 1603 1 126 1.0000 NA 186920 1 83
#> 1604 1 246 1.0000 311200 311200 . 830
#> 1605 1 272 1.0000 NA 176410 1 83
#> 1606 1 705 1.0000 87080 551900 1 83
#> 1607 1 44 1.0000 NA 69160 1 80
#> 1608 1 16 1.0000 NA 15775 1 80
#> 1609 1 221 1.0000 NA 83970 1 80
#> 1610 1 11 1.0000 NA 17600 1 80
#> 1611 1 27 1.0000 NA 55200 1 80
#> 1612 1 130 1.0000 NA 2236 1 80
#> 1613 1 461 1.0000 NA 975200 1 80
#> 1614 1 238 1.0000 NA 410200 1 80
#> 1615 1 104 1.0000 NA 201940 1 80
#> 1616 1 88 1.0000 NA 230727 1 80
#> 1617 1 277 1.0000 NA 92700 1 81
#> 1618 1 1035 1.0000 NA 906995 1 81
#> 1619 1 293 1.0000 NA 253544 1 81
#> 1620 1 116 1.0000 NA 82700 1 81
#> 1621 1 93 1.0000 NA 68000 1 81
#> 1622 1 148 1.0000 NA 242000 1 81
#> 1623 1 267 1.0000 NA 477900 1 81
#> 1624 1 208 1.0000 NA 76935 1 81
#> 1625 1 1272 1.0000 NA 619910 1 81
#> 1626 1 47 1.0000 NA 1155 1 80
#> 1627 1 720 1.0000 NA 509920 1 80
#> 1628 1 58 1.0000 NA 1196 1 80
#> 1629 1 262 1.0000 NA 449400 1 80
#> 1630 1 1283 1.0000 NA 2265400 1 80
#> 1631 1 85 1.0000 NA 219600 1 80
#> 1632 1 134 1.0000 NA 609000 1 80
#> 1633 1 2159 1.0000 NA 1332000 1 80
#> 1634 1 376 1.0000 235700 235700 . 830
#> 1635 1 450 1.0000 256700 256700 . 830
#> 1636 1 361 1.0000 NA 789428 1 83
#> 1637 1 381 1.0000 236700 1078400 1 83
#> 1638 1 97 1.0000 NA 1060 1 78
#> 1639 1 100 1.0000 NA 441 1 78
#> 1640 1 64 1.0000 NA 490 1 78
#> 1641 1 19 1.0000 NA 334 1 78
#> 1642 1 68 1.0000 NA 2535 1 78
#> 1643 1 23 1.0000 NA 260 1 78
#> 1644 1 6 1.0000 NA 232 1 78
#> 1645 1 51 1.0000 NA 1076 1 78
#> 1646 1 138 1.0000 NA 50840 1 78
#> 1647 1 57 1.0000 NA 146199 1 78
#> 1648 1 11 1.0000 28444 28444 . 840
#> 1649 2 30 1.0000 60500 60500 . 840
#> 1650 1 532 1.0000 299300 299300 . 840
#> 1651 2 32 1.0000 72375 72375 . 840
#> 1652 1 340 1.0000 NA 318800 1 84
#> 1653 1 1564 1.0000 NA 1051800 1 84
#> 1654 1 823 1.0000 NA 766200 1 84
#> 1655 1 386 1.0000 NA 624080 1 84
#> 1656 1 281 1.0000 NA 421630 1 84
#> 1657 1 12 1.0000 NA 29300 1 83
#> 1658 1 253 1.0000 NA 265160 1 83
#> 1659 2 37 1.0000 18400 18400 . 830
#> 1660 1 1 1.0000 4666 4666 . 830
#> 1661 1 696 1.0000 366200 366200 . 830
#> 1662 1 260 1.0000 158400 158400 . 830
#> 1663 1 655 1.0000 530200 530200 . 830
#> 1664 1 2531 1.0000 1547900 1547900 . 830
#> 1665 1 928 1.0000 584600 584600 . 830
#> 1666 1 467 1.0000 NA 1845600 1 83
#> 1667 1 413 1.0000 NA 5844000 1 83
#> 1668 1 675 1.0000 494400 494400 . 830
#> 1669 1 964 1.0000 429000 429000 . 830
#> 1670 1 66 1.0000 60700 60700 . 830
#> 1671 1 402 1.0000 255000 255000 . 830
#> 1672 1 3173 1.0000 NA 1888505 1 83
#> 1673 1 486 1.0000 NA 407138 1 83
#> 1674 1 2182 1.0000 NA 1623738 1 83
#> 1675 1 307 1.0000 355358 355358 . 830
#> 1676 1 750 1.0000 NA 524400 1 83
#> 1677 1 382 1.0000 NA 360700 1 83
#> 1678 1 448 1.0000 NA 1280 1 80
#> 1679 1 764 1.0000 NA 209400 1 80
#> 1680 1 114 1.0000 NA 92880 1 80
#> 1681 1 358 1.0000 NA 1040 1 80
#> 1682 1 609 1.0000 NA 7600 1 80
#> 1683 1 9 1.0000 NA 128 1 80
#> 1684 1 421 1.0000 NA 382800 1 80
#> 1685 1 103 1.0000 NA 85500 1 80
#> 1686 1 254 1.0000 NA 2510 1 76
#> 1687 1 293 1.0000 NA 3352 1 76
#> 1688 1 142 1.0000 NA 3942 1 76
#> 1689 1 125 1.0000 NA 3523 1 76
#> 1690 1 164 1.0000 NA 3531 1 76
#> 1691 1 224 1.0000 NA 2201 1 76
#> 1692 1 120 1.0000 NA 2340 1 76
#> 1693 1 41 1.0000 NA 1500 1 76
#> 1694 1 111 1.0000 NA 2800 1 76
#> 1695 1 196 1.0000 NA 4070 1 76
#> 1696 1 26 1.0000 NA 302 1 76
#> 1697 1 1802 1.0000 735500 735500 . 830
#> 1698 1 449 1.0000 255400 255400 . 830
#> 1699 1 1346 1.0000 668600 668600 . 830
#> 1700 1 210 1.0000 NA 4200 1 79
#> 1701 1 261 1.0000 326600 326600 . 790
#> 1702 1 140 1.0000 NA 5860 1 79
#> 1703 1 274 1.0000 221100 221100 . 790
#> 1704 1 1965 1.0000 1978100 1978100 . 790
#> 1705 1 212 1.0000 324500 324500 . 790
#> 1706 1 9 1.0000 7230 7230 . 790
#> 1707 1 200 1.0000 200545 200545 . 790
#> 1708 1 359 1.0000 NA 214200 1 79
#> 1709 1 201 1.0000 NA 769400 1 79
#> 1710 1 165 1.0000 110300 110300 . 780
#> 1711 1 241 1.0000 NA 16680 1 78
#> 1712 1 47 1.0000 NA 991 1 78
#> 1713 1 280 1.0000 145200 145200 . 780
#> 1714 1 551 1.0000 NA 9747 1 78
#> 1715 1 2 1.0000 NA 7700 1 78
#> 1716 1 207 1.0000 NA 7480 1 78
#> 1717 1 225 1.0000 NA 24320 1 78
#> 1718 1 513 1.0000 NA 1068000 1 78
#> 1719 1 204 1.0000 NA 4340 1 78
#> 1720 1 900 1.0000 NA 2694800 1 78
#> 1721 1 51 1.0000 NA 198200 1 78
#> 1722 1 8 1.0000 NA 29131 1 79
#> 1723 1 16 1.0000 NA 15175 1 79
#> 1724 1 76 1.0000 NA 196400 1 79
#> 1725 1 24 1.0000 NA 76400 1 79
#> 1726 1 3 1.0000 NA 17800 1 79
#> 1727 1 21 1.0000 NA 954 1 79
#> 1728 1 561 1.0000 NA 1282400 1 79
#> 1729 1 66 1.0000 NA 159600 1 79
#> 1730 1 11 1.0000 NA 74600 1 79
#> 1731 1 209 1.0000 NA 1074 1 80
#> 1732 1 132 1.0000 NA 61000 1 80
#> 1733 1 205 1.0000 NA 40500 1 80
#> 1734 1 63 1.0000 NA 1001 1 80
#> 1735 1 5 1.0000 NA 9844 1 80
#> 1736 1 438 1.0000 NA 203200 1 80
#> 1737 1 60 1.0000 NA 118971 1 80
#> 1738 1 191 1.0000 NA 1796 1 80
#> 1739 1 275 1.0000 NA 157000 1 80
#> 1740 1 287 1.0000 NA 188000 1 82
#> 1741 1 799 1.0000 NA 663240 1 82
#> 1742 1 50 1.0000 NA 64726 1 82
#> 1743 1 258 1.0000 NA 277092 1 82
#> 1744 1 55 1.0000 NA 132320 1 82
#> 1745 1 855 1.0000 534700 534700 . 810
#> 1746 1 913 1.0000 NA 1100400 1 81
#> 1747 1 72 1.0000 NA 113500 1 81
#> 1748 1 3068 1.0000 1485100 1485100 . 810
#> 1749 1 44 1.0000 NA 53000 1 81
#> 1750 1 541 1.0000 NA 2550 1 81
#> 1751 1 1173 1.0000 490900 490900 . 820
#> 1752 1 163 1.0000 NA 85800 1 82
#> 1753 1 169 1.0000 NA 114200 1 82
#> 1754 1 1636 1.0000 1059232 1059232 . 820
#> 1755 1 39 1.0000 NA 44000 1 82
#> 1756 1 484 1.0000 NA 713056 1 82
#> 1757 1 25 1.0000 NA 42332 1 82
#> 1758 1 390 1.0000 NA 480486 1 82
#> 1759 1 787 1.0000 NA 792680 1 82
#> 1760 1 246 1.0000 311200 311200 . 820
#> 1761 1 2575 1.0000 1652600 1652600 . 820
#> 1762 1 1959 1.0000 NA 629000 1 82
#> 1763 1 70 1.0000 NA 820 1 77
#> 1764 1 471 1.0000 NA 1532 1 77
#> 1765 1 40 1.0000 NA 325 1 77
#> 1766 1 3 1.0000 NA 5199 1 77
#> 1767 1 107 1.0000 NA 54500 1 77
#> 1768 1 1294 1.0000 NA 4143798 1 77
#> 1769 1 322 1.0000 NA 165122 1 80
#> 1770 1 493 1.0000 NA 577785 1 79
#> 1771 1 44 1.0000 NA 48091 1 79
#> 1772 1 145 1.0000 NA 2724 1 79
#> 1773 1 15 1.0000 NA 41300 1 79
#> 1774 1 232 1.0000 NA 763200 1 79
#> 1775 1 36 1.0000 NA 47200 1 79
#> 1776 1 97 1.0000 NA 225199 1 79
#> 1777 1 48 1.0000 NA 156800 1 79
#> 1778 1 985 1.0000 NA 1083199 1 79
#> 1779 1 50 1.0000 NA 262 1 80
#> 1780 1 1272 1.0000 NA 571239 1 80
#> 1781 1 270 1.0000 NA 433200 1 80
#> 1782 1 424 1.0000 NA 1392 1 80
#> 1783 1 974 1.0000 NA 513400 1 80
#> 1784 1 418 1.0000 NA 3924 1 80
#> 1785 1 1958 1.0000 NA 1040200 1 80
#> 1786 1 140 1.0000 NA 81110 1 79
#> 1787 1 47 1.0000 NA 1155 1 79
#> 1788 1 32 1.0000 NA 71900 1 79
#> 1789 1 4 1.0000 NA 20399 1 79
#> 1790 1 720 1.0000 NA 509920 1 79
#> 1791 1 597 1.0000 NA 758000 1 79
#> 1792 1 182 1.0000 NA 314000 1 79
#> 1793 1 208 1.0000 NA 1840 1 79
#> 1794 1 44 1.0000 NA 70000 1 79
#> 1795 1 457 1.0000 NA 42 1 79
#> 1796 1 175 1.0000 NA 234000 1 79
#> 1797 1 511 1.0000 NA 1179400 1 79
#> 1798 1 262 1.0000 NA 449400 1 79
#> 1799 1 44 1.0000 NA 48000 1 79
#> 1800 1 464 1.0000 NA 372800 1 79
#> 1801 1 85 1.0000 NA 219600 1 79
#> 1802 1 134 1.0000 NA 609000 1 79
#> 1803 1 930 1.0000 325700 325700 . 820
#> 1804 1 1869 1.0000 1031500 1031500 . 820
#> 1805 2 388 2.6587 NA 557000 1 82
#> 1806 1 768 1.0000 213450 2338500 1 82
#> 1807 2 20 1.0000 57020 57020 . 830
#> 1808 2 48 1.0000 89700 89700 . 830
#> 1809 1 1564 1.0000 NA 1051800 1 83
#> 1810 1 324 1.0000 NA 124000 1 83
#> 1811 1 1243 1.0000 314690 314690 . 830
#> 1812 1 478 1.0000 NA 1010224 1 83
#> 1813 1 283 1.0000 NA 231726 1 83
#> 1814 1 656 1.0000 NA 468400 1 83
#> 1815 1 510 1.0000 NA 1273480 1 83
#> 1816 1 96 1.0000 NA 178264 1 83
#> 1817 1 612 1.0000 NA 2470000 1 83
#> 1818 1 11 1.0000 NA 168 1 77
#> 1819 1 73 1.0000 NA 429 1 77
#> 1820 1 124 1.0000 NA 716 1 77
#> 1821 1 32 1.0000 NA 448 1 77
#> 1822 1 97 1.0000 NA 1060 1 77
#> 1823 1 26 1.0000 NA 293 1 77
#> 1824 1 48 1.0000 NA 701 1 77
#> 1825 1 51 1.0000 NA 630 1 77
#> 1826 1 46 1.0000 NA 513 1 77
#> 1827 1 68 1.0000 NA 2535 1 77
#> 1828 1 51 1.0000 NA 1076 1 77
#> 1829 1 188 1.0000 NA 226300 1 77
#> 1830 1 706 1.0000 367200 367200 . 820
#> 1831 1 370 1.0000 173800 173800 . 820
#> 1832 1 362 1.0000 NA 402940 1 82
#> 1833 2 35 1.0000 94600 94600 . 820
#> 1834 1 145 1.0000 64800 64800 . 820
#> 1835 1 150 1.0000 NA 173300 1 82
#> 1836 1 703 1.0000 320500 320500 . 820
#> 1837 1 860 1.0000 365200 365200 . 820
#> 1838 1 402 1.0000 255000 255000 . 820
#> 1839 1 307 1.0000 355358 355358 . 820
#> 1840 1 1067 1.0000 NA 602200 1 82
#> 1841 1 727 1.0000 502400 502400 . 820
#> 1842 1 646 1.0000 409300 409300 . 820
#> 1843 1 1955 1.0000 1222200 1222200 . 820
#> 1844 1 2531 1.0000 1547900 1547900 . 820
#> 1845 1 467 1.0000 NA 1845600 1 82
#> 1846 1 413 1.0000 NA 5844000 1 82
#> 1847 1 549 1.0000 409900 409900 . 820
#> 1848 1 794 1.0000 525300 525300 . 820
#> 1849 1 964 1.0000 429000 429000 . 820
#> 1850 1 279 1.0000 NA 3500 1 79
#> 1851 1 282 1.0000 NA 262200 1 79
#> 1852 1 6 1.0000 NA 162 1 79
#> 1853 1 449 1.0000 255400 255400 . 820
#> 1854 1 32 1.0000 24790 49580 1 82
#> 1855 1 2507 1.0000 1074400 1074400 . 820
#> 1856 2 377 2.0290 NA 363200 1 82
#> 1857 1 50 1.0000 NA 624 1 75
#> 1858 1 254 1.0000 NA 2510 1 75
#> 1859 1 68 1.0000 NA 1376 1 75
#> 1860 1 293 1.0000 NA 3352 1 75
#> 1861 1 82 1.0000 NA 854 1 75
#> 1862 1 142 1.0000 NA 3942 1 75
#> 1863 1 125 1.0000 NA 3523 1 75
#> 1864 1 164 1.0000 NA 3531 1 75
#> 1865 1 120 1.0000 NA 2340 1 75
#> 1866 1 111 1.0000 NA 2800 1 75
#> 1867 1 196 1.0000 NA 4070 1 75
#> 1868 1 81 1.0000 NA 1300 1 75
#> 1869 1 213 1.0000 NA 2960 1 75
#> 1870 1 121 1.0000 NA 1430 1 75
#> 1871 1 130 1.0000 NA 3080 1 75
#> 1872 1 11 1.0000 NA 160 1 75
#> 1873 1 106 1.0000 NA 1300 1 75
#> 1874 1 136 1.0000 NA 1000 1 75
#> 1875 1 1 1.0000 NA 52 1 75
#> 1876 1 23 1.0000 NA 600 1 75
#> 1877 1 71 1.0000 NA 193900 1 75
#> 1878 1 119 1.0000 NA 1000 1 75
#> 1879 1 96 1.0000 NA 317000 1 75
#> 1880 1 40 1.0000 NA 126200 1 75
#> 1881 1 67 1.0000 NA 801 1 75
#> 1882 1 84 1.0000 NA 801 1 75
#> 1883 1 45 1.0000 NA 804 1 75
#> 1884 1 480 1.0000 364500 364500 . 780
#> 1885 1 91 1.0000 68700 68700 . 780
#> 1886 1 35 1.0000 99030 99030 . 780
#> 1887 1 1965 1.0000 1978100 1978100 . 780
#> 1888 1 7 1.0000 NA 208 1 78
#> 1889 1 162 1.0000 NA 8834 1 78
#> 1890 1 192 1.0000 NA 385600 1 78
#> 1891 1 279 1.0000 NA 388000 1 78
#> 1892 1 1456 1.0000 NA 1145200 1 78
#> 1893 1 352 1.0000 NA 253800 1 78
#> 1894 1 201 1.0000 NA 769400 1 78
#> 1895 1 429 1.0000 NA 650000 1 78
#> 1896 1 262 1.0000 118100 118100 . 820
#> 1897 1 266 1.0000 117400 117400 . 820
#> 1898 1 180 1.0000 194500 194500 . 770
#> 1899 1 241 1.0000 NA 16680 1 77
#> 1900 1 155 1.0000 NA 1570 1 77
#> 1901 1 35 1.0000 NA 871 1 77
#> 1902 1 184 1.0000 NA 2552 1 77
#> 1903 1 68 1.0000 NA 192100 1 77
#> 1904 1 24 1.0000 NA 73900 1 77
#> 1905 1 124 1.0000 NA 3853 1 77
#> 1906 1 363 1.0000 NA 691000 1 77
#> 1907 1 513 1.0000 NA 1068000 1 77
#> 1908 1 900 1.0000 NA 2694800 1 77
#> 1909 1 51 1.0000 NA 198200 1 77
#> 1910 1 458 1.0000 NA 68970 1 78
#> 1911 1 3 1.0000 NA 173 1 78
#> 1912 1 260 1.0000 NA 785000 1 78
#> 1913 1 3 1.0000 NA 16900 1 78
#> 1914 1 41 1.0000 NA 23100 1 78
#> 1915 1 21 1.0000 NA 954 1 78
#> 1916 1 123 1.0000 NA 1662 1 78
#> 1917 1 304 1.0000 NA 561800 1 78
#> 1918 1 178 1.0000 NA 226800 1 78
#> 1919 1 66 1.0000 NA 159600 1 78
#> 1920 1 335 1.0000 NA 378300 1 78
#> 1921 1 263 1.0000 NA 181400 1 78
#> 1922 1 27 1.0000 NA 117353 1 78
#> 1923 1 209 1.0000 NA 599200 1 78
#> HLNoAtLngt DevStage LenMeasType DateofCalculation Valid_Aphia Ship2 Ship3
#> 1 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 2 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 3 2.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 4 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 5 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 6 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 7 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 8 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 9 2.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 10 3.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 11 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 12 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 13 1.00 <NA> NA 20211203 126436 ARG ARG
#> 14 2.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 15 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 16 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 17 2.00 <NA> NA 20140617 126436 ARG ARG
#> 18 2.00 <NA> NA 20211203 126436 SOL SOL
#> 19 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 20 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 21 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 22 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 23 2.00 <NA> NA 20131112 126436 ARG ARG
#> 24 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 25 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 26 1.00 <NA> NA 20211203 126436 SOL SOL
#> 27 2.00 <NA> NA 20131113 126436 ARG ARG
#> 28 2.00 <NA> NA 20190228 126436 ARG ARG
#> 29 2.00 <NA> NA 20190228 126436 ARG ARG
#> 30 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 31 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 32 2.00 <NA> NA 20161115 126436 ARG ARG
#> 33 2.00 <NA> NA 20161115 126436 ARG ARG
#> 34 2.00 <NA> NA 20131112 126436 ARG ARG
#> 35 2.00 <NA> NA 20140617 126436 ARG ARG
#> 36 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 37 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 38 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 39 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 40 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 41 1.00 <NA> NA 20211203 126436 SOL SOL
#> 42 1.00 <NA> NA 20211203 126436 SOL SOL
#> 43 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 44 2.00 <NA> NA 20140617 126436 ARG ARG
#> 45 2.00 <NA> NA 20161213 126436 SOL SOL
#> 46 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 47 1.00 <NA> NA 20211203 126436 ARG ARG
#> 48 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 49 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 50 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 51 1.00 <NA> NA 20211203 126436 LAIZ LAIZ
#> 52 3.00 <NA> NA 20131111 126436 ARG ARG
#> 53 2.00 <NA> NA 20180507 126436 BAL BAL
#> 54 3.00 <NA> NA 20140617 126436 ATLD ATLD
#> 55 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 56 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 57 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 58 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 59 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 60 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 61 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 62 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 63 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 64 2.00 <NA> NA 20190208 126436 ARG ARG
#> 65 2.00 <NA> NA 20160721 126436 BAL BAL
#> 66 1.00 <NA> NA 20211203 126436 ARG ARG
#> 67 2.00 <NA> NA 20140617 126436 ARG ARG
#> 68 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 69 2.00 <NA> NA 20180423 126436 ATL ATL
#> 70 2.00 <NA> NA 20131216 126436 ARG ARG
#> 71 1.00 <NA> NA 20211203 126436 SOL SOL
#> 72 2.00 <NA> NA 20161115 126436 SOL SOL
#> 73 2.00 <NA> NA 20161115 126436 ARG ARG
#> 74 2.00 <NA> NA 20131112 126436 ARG ARG
#> 75 2.00 <NA> NA 20160721 126436 BAL BAL
#> 76 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 77 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 78 2.00 <NA> NA 20161213 126436 SOL SOL
#> 79 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 80 2.00 <NA> NA 20190208 126436 ARG ARG
#> 81 2.00 <NA> NA 20140611 126436 BAL BAL
#> 82 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 83 2.00 <NA> NA 20161115 126436 ARG ARG
#> 84 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 85 16.00 <NA> NA 20180423 126436 ATL ATL
#> 86 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 87 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 88 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 89 2.00 <NA> NA 20161213 126436 BAL BAL
#> 90 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 91 2.00 <NA> NA 20140616 126436 ATL ATL
#> 92 2.00 <NA> NA 20211203 126436 SOL SOL
#> 93 2.00 <NA> NA 20160714 126436 SOL SOL
#> 94 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 95 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 96 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 97 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 98 2.00 <NA> NA 20140611 126436 ATLD ATLD
#> 99 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 100 4.00 <NA> NA 20190208 126436 SOL SOL
#> 101 2.00 <NA> NA 20161115 126436 ARG ARG
#> 102 2.00 <NA> NA 20161115 126436 SOL SOL
#> 103 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 104 1.00 <NA> NA 20211203 126436 SOL SOL
#> 105 2.00 <NA> NA 20140616 126436 BAL BAL
#> 106 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 107 2.00 <NA> NA 20140617 126436 ARG ARG
#> 108 2.00 <NA> NA 20190207 126436 ARG ARG
#> 109 2.00 <NA> NA 20200115 126436 ARG ARG
#> 110 2.00 <NA> NA 20160714 126436 ATL ATL
#> 111 2.00 <NA> NA 20180507 126436 BAL BAL
#> 112 2.00 <NA> NA 20180507 126436 BAL BAL
#> 113 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 114 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 115 1.00 <NA> NA 20211203 126436 SOL SOL
#> 116 1.00 <NA> NA 20211203 126436 ARG ARG
#> 117 2.00 <NA> NA 20131112 126436 ARG ARG
#> 118 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 119 2.00 <NA> NA 20140617 126436 SOL SOL
#> 120 2.00 <NA> NA 20140617 126436 ARG ARG
#> 121 4.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 122 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 123 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 124 2.00 <NA> NA 20131216 126436 BAL BAL
#> 125 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 126 1.00 <NA> NA 20211203 126436 SOL SOL
#> 127 1.00 <NA> NA 20211203 126436 ARG ARG
#> 128 4.00 <NA> NA 20190228 126436 ATL ATL
#> 129 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 130 1.00 <NA> NA 20160721 126436 SOL SOL
#> 131 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 132 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 133 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 134 2.00 <NA> NA 20140616 126436 SOL SOL
#> 135 2.00 <NA> NA 20140616 126436 BAL BAL
#> 136 1.00 <NA> NA 20211203 126436 SOL SOL
#> 137 1.00 <NA> NA 20211203 126436 SOL SOL
#> 138 2.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 139 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 140 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 141 2.00 <NA> NA 20161115 126436 ARG ARG
#> 142 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 143 2.00 <NA> NA 20180507 126436 BAL BAL
#> 144 3.00 <NA> NA 20190228 126436 ATL ATL
#> 145 2.00 <NA> NA 20190228 126436 ARG ARG
#> 146 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 147 1.00 <NA> NA 20211203 126436 SOL SOL
#> 148 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 149 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 150 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 151 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 152 2.00 <NA> NA 20161115 126436 ARG ARG
#> 153 1.76 <NA> NA 20161115 126436 ARG ARG
#> 154 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 155 2.00 <NA> NA 20140617 126436 BAL BAL
#> 156 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 157 2.00 <NA> NA 20131112 126436 ARG ARG
#> 158 2.00 <NA> NA 20131112 126436 ARG ARG
#> 159 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 160 2.00 <NA> NA 20140616 126436 SOL SOL
#> 161 2.00 <NA> NA 20140616 126436 BAL BAL
#> 162 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 163 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 164 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 165 2.00 <NA> NA 20190207 126436 ARG ARG
#> 166 1.00 <NA> NA 20131108 126436 SOL SOL
#> 167 2.00 <NA> NA 20161213 126436 SOL SOL
#> 168 2.00 <NA> NA 20161115 126436 ARG ARG
#> 169 1.00 <NA> NA 20160721 126436 SOL SOL
#> 170 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 171 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 172 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 173 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 174 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 175 2.00 <NA> NA 20190208 126436 ARG ARG
#> 176 2.00 <NA> NA 20161115 126436 ARG ARG
#> 177 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 178 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 179 2.00 <NA> NA 20190207 126436 ARG ARG
#> 180 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 181 2.00 <NA> NA 20161115 126436 ARG ARG
#> 182 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 183 1.00 <NA> NA 20211203 126436 SOL SOL
#> 184 2.00 <NA> NA 20211203 126436 SOL SOL
#> 185 1.00 <NA> NA 20211203 126436 ARG ARG
#> 186 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 187 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 188 2.00 <NA> NA 20161213 126436 ARG ARG
#> 189 2.00 <NA> NA 20180507 126436 ARG ARG
#> 190 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 191 2.00 <NA> NA 20190228 126436 ARG ARG
#> 192 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 193 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 194 1.00 <NA> NA 20211203 126436 SOL SOL
#> 195 1.00 <NA> NA 20211203 126436 SOL SOL
#> 196 2.00 <NA> NA 20131111 126436 SOL SOL
#> 197 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 198 2.00 <NA> NA 20161115 126436 ARG ARG
#> 199 2.00 <NA> NA 20161115 126436 ARG ARG
#> 200 1.00 <NA> NA 20131204 126436 SOL2 SOL2
#> 201 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 202 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 203 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 204 2.00 <NA> NA 20140617 126436 BAL BAL
#> 205 2.00 <NA> NA 20140617 126436 ARG ARG
#> 206 2.00 <NA> NA 20131112 126436 ARG ARG
#> 207 2.00 <NA> NA 20131112 126436 ARG ARG
#> 208 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 209 2.00 <NA> NA 20140616 126436 BAL BAL
#> 210 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 211 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 212 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 213 1.00 <NA> NA 20211203 126436 SOL SOL
#> 214 1.00 <NA> NA 20211203 126436 SOL SOL
#> 215 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 216 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 217 2.00 <NA> NA 20131113 126436 SOL SOL
#> 218 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 219 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 220 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 221 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 222 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 223 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 224 2.00 <NA> NA 20160721 126436 BAL BAL
#> 225 2.00 <NA> NA 20180507 126436 ATL ATL
#> 226 2.00 <NA> NA 20190228 126436 AA36 AA36
#> 227 2.00 <NA> NA 20190228 126436 ARG ARG
#> 228 2.00 <NA> NA 20190208 126436 ARG ARG
#> 229 2.00 <NA> NA 20131216 126436 BAL BAL
#> 230 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 231 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 232 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 233 5.00 <NA> NA 20180507 126436 ATLD ATLD
#> 234 2.00 <NA> NA 20140617 126436 BAL BAL
#> 235 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 236 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 237 2.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 238 2.00 <NA> NA 20140611 126436 77MA 77MA
#> 239 2.00 <NA> NA 20140611 126436 ATLD ATLD
#> 240 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 241 2.00 <NA> NA 20190207 126436 SOL SOL
#> 242 2.00 <NA> NA 20190207 126436 SOL SOL
#> 243 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 244 1.00 <NA> NA 20131113 126436 SOL SOL
#> 245 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 246 2.00 <NA> NA 20211203 126436 ARG ARG
#> 247 1.00 <NA> NA 20211203 126436 ARG ARG
#> 248 2.60 <NA> NA 20161213 126436 ARG ARG
#> 249 4.00 <NA> NA 20161115 126436 SOL SOL
#> 250 1.00 <NA> NA 20211203 126436 SOL SOL
#> 251 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 252 2.00 <NA> NA 20190228 126436 SOL SOL
#> 253 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 254 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 255 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 256 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 257 2.00 <NA> NA 20190208 126436 ARG ARG
#> 258 2.00 <NA> NA 20161115 126436 ARG ARG
#> 259 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 260 2.00 <NA> NA 20180423 126436 BAL BALL
#> 261 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 262 2.00 <NA> NA 20180507 126436 BAL BAL
#> 263 1.00 <NA> NA 20211203 126436 ARG ARG
#> 264 2.40 <NA> NA 20131204 126436 ARG ARG
#> 265 2.00 <NA> NA 20131204 126436 ATL ATL
#> 266 2.00 <NA> NA 20131216 126436 BAL BAL
#> 267 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 268 2.00 <NA> NA 20140617 126436 SOL SOL
#> 269 2.00 <NA> NA 20140617 126436 ARG ARG
#> 270 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 271 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 272 2.00 <NA> NA 20140616 126436 SOL SOL
#> 273 2.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 274 2.00 <NA> NA 20140616 126436 ARG ARG
#> 275 6.00 <NA> NA 20140611 126436 BAL BAL
#> 276 2.00 <NA> NA 20131108 126436 ATL ATL
#> 277 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 278 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 279 2.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 280 2.00 <NA> NA 20131204 126436 BAL BAL
#> 281 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 282 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 283 2.00 <NA> NA 20161115 126436 ARG ARG
#> 284 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 285 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 286 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 287 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 288 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 289 1.00 <NA> NA 20160721 126436 SOL SOL
#> 290 2.00 <NA> NA 20131216 126436 ARG ARG
#> 291 2.00 <NA> NA 20161115 126436 SOL SOL
#> 292 2.00 <NA> NA 20131216 126436 BAL BAL
#> 293 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 294 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 295 2.00 <NA> NA 20161115 126436 BAL BAL
#> 296 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 297 2.00 <NA> NA 20161115 126436 BAL BAL
#> 298 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 299 1.00 <NA> NA 20211203 126436 ARG ARG
#> 300 2.00 <NA> NA 20140617 126436 ARG ARG
#> 301 2.00 <NA> NA 20131112 126436 SOL SOL
#> 302 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 303 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 304 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 305 2.00 <NA> NA 20131113 126436 ARG ARG
#> 306 2.00 <NA> NA 20161213 126436 ARG ARG
#> 307 2.00 <NA> NA 20161115 126436 ARG ARG
#> 308 2.00 <NA> NA 20161115 126436 ARG ARG
#> 309 2.00 <NA> NA 20180423 126436 ATL ATL
#> 310 2.00 <NA> NA 20211203 126436 ARG ARG
#> 311 1.00 <NA> NA 20211203 126436 ARG ARG
#> 312 1.00 <NA> NA 20211203 126436 ARG ARG
#> 313 1.00 <NA> NA 20211203 126436 ARG ARG
#> 314 2.00 <NA> NA 20160721 126436 BAL BAL
#> 315 2.00 <NA> NA 20180507 126436 BAL BAL
#> 316 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 317 1.00 <NA> NA 20211203 126436 SOL SOL
#> 318 1.00 <NA> NA 20211203 126436 SOL SOL
#> 319 2.00 <NA> NA 20190228 126436 SOL SOL
#> 320 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 321 2.00 <NA> NA 20190228 126436 ARG ARG
#> 322 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 323 5.00 <NA> NA 20180507 126436 ATLD ATLD
#> 324 2.00 <NA> NA 20190208 126436 SOL SOL
#> 325 2.00 <NA> NA 20161115 126436 SOL SOL
#> 326 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 327 2.00 <NA> NA 20161115 126436 ARG ARG
#> 328 2.00 <NA> NA 20161115 126436 ARG ARG
#> 329 1.00 <NA> NA 20211203 126436 ARG ARG
#> 330 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 331 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 332 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 333 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 334 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 335 2.00 <NA> NA 20131113 126436 ARG ARG
#> 336 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 337 2.00 <NA> NA 20161213 126436 ARG ARG
#> 338 2.00 <NA> NA 20161115 126436 ARG ARG
#> 339 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 340 2.00 <NA> NA 20190207 126436 ARG ARG
#> 341 1.00 <NA> NA 20211203 126436 ARG ARG
#> 342 1.00 <NA> NA 20211203 126436 ARG ARG
#> 343 4.00 <NA> NA 20131111 126436 SOL SOL
#> 344 2.00 <NA> NA 20180507 126436 BAL BAL
#> 345 2.00 <NA> NA 20180507 126436 BAL BAL
#> 346 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 347 2.00 <NA> NA 20190228 126436 ARG ARG
#> 348 2.00 <NA> NA 20131112 126436 ARG ARG
#> 349 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 350 1.00 <NA> NA 20211203 126436 SOL SOL
#> 351 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 352 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 353 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 354 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 355 2.00 <NA> NA 20160721 126436 BAL BAL
#> 356 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 357 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 358 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 359 2.00 <NA> NA 20190208 126436 ARG ARG
#> 360 2.00 <NA> NA 20161115 126436 ATL ATL
#> 361 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 362 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 363 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 364 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 365 2.00 <NA> NA 20140617 126436 ARG ARG
#> 366 2.00 <NA> NA 20140617 126436 BAL BAL
#> 367 2.00 <NA> NA 20140617 126436 ARG ARG
#> 368 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 369 2.00 <NA> NA 20131112 126436 ARG ARG
#> 370 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 371 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 372 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 373 2.00 <NA> NA 20131112 126436 ARG ARG
#> 374 2.00 <NA> NA 20131112 126436 ARG ARG
#> 375 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 376 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 377 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 378 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 379 2.00 <NA> NA 20161213 126436 ARG ARG
#> 380 2.00 <NA> NA 20160721 126436 ARG ARG
#> 381 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 382 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 383 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 384 2.00 <NA> NA 20161115 126436 ARG ARG
#> 385 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 386 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 387 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 388 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 389 1.00 <NA> NA 20211203 126436 ARG ARG
#> 390 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 391 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 392 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 393 2.00 <NA> NA 20190228 126436 ATL ATL
#> 394 2.00 <NA> NA 20131216 126436 BAL BAL
#> 395 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 396 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 397 2.00 <NA> NA 20131216 126436 ARG ARG
#> 398 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 399 2.00 <NA> NA 20160721 126436 BAL BAL
#> 400 2.00 <NA> NA 20161115 126436 ARG ARG
#> 401 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 402 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 403 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 404 2.00 <NA> NA 20131111 126436 SOL SOL
#> 405 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 406 2.00 <NA> NA 20161115 126436 BAL BAL
#> 407 2.00 <NA> NA 20161115 126436 ATL ATL
#> 408 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 409 5.00 <NA> NA 20131111 126436 SOL SOL
#> 410 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 411 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 412 2.00 <NA> NA 20140617 126436 SOL SOL
#> 413 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 414 2.00 <NA> NA 20140617 126436 ARG ARG
#> 415 2.00 <NA> NA 20140616 126436 BAL BAL
#> 416 2.00 <NA> NA 20140616 126436 BAL BAL
#> 417 2.00 <NA> NA 20140616 126436 ARG ARG
#> 418 3.00 <NA> NA 20180423 126436 ATL ATL
#> 419 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 420 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 421 2.00 <NA> NA 20131108 126436 SOL SOL
#> 422 2.00 <NA> NA 20131108 126436 ARG ARG
#> 423 2.00 <NA> NA 20131204 126436 ARG ARG
#> 424 2.00 <NA> NA 20131204 126436 ARG ARG
#> 425 2.00 <NA> NA 20131113 126436 ARG ARG
#> 426 2.00 <NA> NA 20140219 126436 ATL ATL
#> 427 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 428 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 429 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 430 4.00 <NA> NA 20180507 126436 BAL BAL
#> 431 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 432 5.00 <NA> NA 20180507 126436 ATLD ATLD
#> 433 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 434 3.00 <NA> NA 20190207 126436 RUEK RUEK
#> 435 2.00 <NA> NA 20190207 126436 ARG ARG
#> 436 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 437 1.00 <NA> NA 20211203 126436 ARG ARG
#> 438 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 439 2.00 <NA> NA 20131204 126436 BAL BAL
#> 440 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 441 2.00 <NA> NA 20131216 126436 BAL BAL
#> 442 2.00 <NA> NA 20131216 126436 BAL BAL
#> 443 3.00 <NA> NA 20131216 126436 ATL ATL
#> 444 2.00 <NA> NA 20131216 126436 ARG ARG
#> 445 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 446 2.00 <NA> NA 20131112 126436 ARG ARG
#> 447 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 448 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 449 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 450 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 451 2.00 <NA> NA 20190208 126436 ARG ARG
#> 452 2.00 <NA> NA 20190208 126436 ARG ARG
#> 453 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 454 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 455 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 456 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 457 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 458 1.00 <NA> NA 20211203 126436 SOL SOL
#> 459 1.00 <NA> NA 20211203 126436 SOL SOL
#> 460 1.00 <NA> NA 20211203 126436 SOL SOL
#> 461 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 462 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 463 2.00 <NA> NA 20161115 126436 BAL BAL
#> 464 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 465 2.00 <NA> NA 20161115 126436 BAL BAL
#> 466 4.00 <NA> NA 20161115 126436 ARG ARG
#> 467 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 468 1.00 <NA> NA 20211203 126436 SOL SOL
#> 469 1.00 <NA> NA 20211203 126436 SOL SOL
#> 470 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 471 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 472 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 473 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 474 2.00 <NA> NA 20140617 126436 BAL BAL
#> 475 6.00 <NA> NA 20140617 126436 ATLD ATLD
#> 476 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 477 2.00 <NA> NA 20140616 126436 BAL BAL
#> 478 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 479 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 480 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 481 1.00 <NA> NA 20131108 126436 SOL SOL
#> 482 1.00 <NA> NA 20131108 126436 SOL SOL
#> 483 2.00 <NA> NA 20131108 126436 ATL ATL
#> 484 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 485 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 486 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 487 2.00 <NA> NA 20131113 126436 ARG ARG
#> 488 3.32 <NA> NA 20131113 126436 ARG ARG
#> 489 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 490 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 491 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 492 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 493 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 494 2.00 <NA> NA 20161213 126436 SOL SOL
#> 495 2.00 <NA> NA 20161213 126436 ARG ARG
#> 496 2.00 <NA> NA 20161213 126436 BAL BAL
#> 497 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 498 2.00 <NA> NA 20180507 126436 BAL BAL
#> 499 2.00 <NA> NA 20180507 126436 BAL BAL
#> 500 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 501 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 502 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 503 2.00 <NA> NA 20190207 126436 ARG ARG
#> 504 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 505 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 506 2.00 <NA> NA 20160721 126436 ARG ARG
#> 507 2.00 <NA> NA 20160721 126436 BAL BAL
#> 508 2.00 <NA> NA 20190228 126436 SOL SOL
#> 509 3.00 <NA> NA 20190228 126436 ATL ATL
#> 510 2.00 <NA> NA 20190228 126436 ARG ARG
#> 511 2.00 <NA> NA 20190228 126436 ARG ARG
#> 512 2.00 <NA> NA 20131112 126436 SOL SOL
#> 513 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 514 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 515 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 516 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 517 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 518 2.00 <NA> NA 20190208 126436 ARG ARG
#> 519 2.00 <NA> NA 20161115 126436 BAL BAL
#> 520 2.00 <NA> NA 20161115 126436 ARG ARG
#> 521 2.00 <NA> NA 20161115 126436 ARG ARG
#> 522 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 523 1.00 <NA> NA 20211203 126436 SOL SOL
#> 524 1.00 <NA> NA 20211203 126436 SOL SOL
#> 525 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 526 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 527 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 528 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 529 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 530 1.00 <NA> NA 20211203 126436 SOL SOL
#> 531 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 532 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 533 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 534 2.00 <NA> NA 20140617 126436 BAL BAL
#> 535 2.00 <NA> NA 20140617 126436 ARG ARG
#> 536 2.00 <NA> NA 20140617 126436 ARG ARG
#> 537 6.00 <NA> NA 20140617 126436 ATLD ATLD
#> 538 2.00 <NA> NA 20131112 126436 SOL SOL
#> 539 2.00 <NA> NA 20140616 126436 BAL BAL
#> 540 2.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 541 2.00 <NA> NA 20131112 126436 ARG ARG
#> 542 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 543 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 544 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 545 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 546 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 547 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 548 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 549 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 550 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 551 2.00 <NA> NA 20131216 126436 BAL BAL
#> 552 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 553 1.00 <NA> NA 20131108 126436 SOL SOL
#> 554 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 555 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 556 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 557 2.00 <NA> NA 20200115 126436 BAL BAL
#> 558 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 559 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 560 4.00 <NA> NA 20180423 126436 BAL BAL
#> 561 2.00 <NA> NA 20180423 126436 BAL BAL
#> 562 1.00 <NA> NA 20180507 126436 SOL2 SOL2
#> 563 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 564 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 565 2.00 <NA> NA 20180507 126436 BAL BAL
#> 566 4.00 <NA> NA 20180507 126436 BAL BALL
#> 567 1.00 <NA> NA 20160721 126436 SOL SOL
#> 568 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 569 2.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 570 2.00 <NA> NA 20161213 126436 BAL BAL
#> 571 2.00 <NA> NA 20161213 126436 BAL BAL
#> 572 2.00 <NA> NA 20190607 126436 BAL BAL
#> 573 2.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 574 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 575 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 576 10.00 <NA> NA 20131204 126436 ATL ATL
#> 577 2.00 <NA> NA 20131216 126436 BAL BAL
#> 578 2.00 <NA> NA 20131216 126436 BAL BAL
#> 579 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 580 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 581 2.00 <NA> NA 20190207 126436 ARG ARG
#> 582 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 583 2.00 <NA> NA 20161115 126436 ARG ARG
#> 584 2.00 <NA> NA 20161115 126436 ARG ARG
#> 585 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 586 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 587 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 588 2.00 <NA> NA 20131216 126436 ATL ATL
#> 589 2.00 <NA> NA 20131216 126436 ARG ARG
#> 590 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 591 2.00 <NA> NA 20160721 126436 BAL BAL
#> 592 2.00 <NA> NA 20190228 126436 SOL SOL
#> 593 2.00 <NA> NA 20190228 126436 ATL ATL
#> 594 2.00 <NA> NA 20190228 126436 ATL ATL
#> 595 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 596 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 597 1.00 <NA> NA 20211203 126436 LAIZ LAIZ
#> 598 1.00 <NA> NA 20211203 126436 ARG ARG
#> 599 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 600 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 601 2.00 <NA> NA 20161115 126436 BAL BAL
#> 602 2.00 <NA> NA 20161115 126436 ATL ATL
#> 603 2.00 <NA> NA 20161115 126436 ATL ATL
#> 604 2.00 <NA> NA 20161115 126436 ARG ARG
#> 605 2.00 <NA> NA 20161115 126436 ARG ARG
#> 606 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 607 3.00 <NA> NA 20140611 126436 BAL BAL
#> 608 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 609 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 610 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 611 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 612 1.00 <NA> NA 20211203 126436 SOL SOL
#> 613 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 614 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 615 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 616 2.00 <NA> NA 20131113 126436 ARG ARG
#> 617 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 618 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 619 4.00 <NA> NA 20140617 126436 ATLD ATLD
#> 620 2.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 621 1.00 <NA> NA 20211203 126436 ARG ARG
#> 622 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 623 2.00 <NA> NA 20140219 126436 BAL BAL
#> 624 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 625 3.00 <NA> NA 20131216 126436 BAL BAL
#> 626 2.00 <NA> NA 20131216 126436 BAL BAL
#> 627 2.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 628 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 629 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 630 2.00 <NA> NA 20180507 126436 BAL BAL
#> 631 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 632 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 633 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 634 2.00 <NA> NA 20131113 126436 BAL BAL
#> 635 2.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 636 2.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 637 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 638 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 639 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 640 2.00 <NA> NA 20160721 126436 BAL BAL
#> 641 2.00 <NA> NA 20180507 126436 BAL BAL
#> 642 2.00 <NA> NA 20180507 126436 BAL BAL
#> 643 2.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 644 5.00 <NA> NA 20180507 126436 BAL BAL
#> 645 2.00 <NA> NA 20131204 126436 BAL BAL
#> 646 2.00 <NA> NA 20131204 126436 ATL ATL
#> 647 2.00 <NA> NA 20131216 126436 BAL BAL
#> 648 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 649 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 650 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 651 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 652 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 653 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 654 2.00 <NA> NA 20190207 126436 ARG ARG
#> 655 2.00 <NA> NA 20190228 126436 ARG ARG
#> 656 2.00 <NA> NA 20211203 126436 SOL SOL
#> 657 1.00 <NA> NA 20211203 126436 ARG ARG
#> 658 1.00 <NA> NA 20211203 126436 ARG ARG
#> 659 1.00 <NA> NA 20211203 126436 ARG ARG
#> 660 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 661 2.00 <NA> NA 20190208 126436 SOL SOL
#> 662 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 663 2.00 <NA> NA 20190208 126436 ARG ARG
#> 664 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 665 2.00 <NA> NA 20190208 126436 ARG ARG
#> 666 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 667 2.00 <NA> NA 20161115 126436 ARG ARG
#> 668 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 669 2.00 <NA> NA 20140611 126436 BAL BAL
#> 670 2.00 <NA> NA 20160714 126436 SOL SOL
#> 671 2.00 <NA> NA 20131113 126436 ARG ARG
#> 672 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 673 3.00 <NA> NA 20180423 126436 ATL ATL
#> 674 2.00 <NA> NA 20180423 126436 ATL ATL
#> 675 4.00 <NA> NA 20180423 126436 BAL BAL
#> 676 2.00 <NA> NA 20180423 126436 ARG ARG
#> 677 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 678 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 679 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 680 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 681 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 682 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 683 2.00 <NA> NA 20211203 126436 SOL SOL
#> 684 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 685 1.00 <NA> NA 20211203 126436 SOL SOL
#> 686 2.00 <NA> NA 20211203 126436 SOL SOL
#> 687 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 688 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 689 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 690 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 691 2.00 <NA> NA 20140617 126436 SOL SOL
#> 692 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 693 2.00 <NA> NA 20140617 126436 ARG ARG
#> 694 2.00 <NA> NA 20140617 126436 BAL BAL
#> 695 4.00 <NA> NA 20140617 126436 BAL BAL
#> 696 6.00 <NA> NA 20140617 126436 ATLD ATLD
#> 697 4.00 <NA> NA 20140617 126436 ATLD ATLD
#> 698 2.00 <NA> NA 20140219 126436 ATL ATL
#> 699 3.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 700 2.00 <NA> NA 20131216 126436 BAL BAL
#> 701 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 702 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 703 2.00 <NA> NA 20131216 126436 BAL BAL
#> 704 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 705 1.00 <NA> NA 20211203 126436 SOL SOL
#> 706 1.00 <NA> NA 20211203 126436 SOL SOL
#> 707 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 708 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 709 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 710 1.00 <NA> NA 20211203 126436 ARG ARG
#> 711 1.00 <NA> NA 20211203 126436 ARG ARG
#> 712 1.00 <NA> NA 20211203 126436 ARG ARG
#> 713 2.00 <NA> NA 20180507 126436 BAL BAL
#> 714 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 715 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 716 2.00 <NA> NA 20140616 126436 SOL SOL
#> 717 2.00 <NA> NA 20140616 126436 SOL SOL
#> 718 2.00 <NA> NA 20140616 126436 ARG ARG
#> 719 2.00 <NA> NA 20131112 126436 ARG ARG
#> 720 2.00 <NA> NA 20131112 126436 ARG ARG
#> 721 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 722 2.00 <NA> NA 20131113 126436 ARG ARG
#> 723 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 724 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 725 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 726 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 727 2.00 <NA> NA 20161213 126436 ARG ARG
#> 728 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 729 2.00 <NA> NA 20131204 126436 ATL ATL
#> 730 3.00 <NA> NA 20131204 126436 BAL BAL
#> 731 2.00 <NA> NA 20131204 126436 BAL BAL
#> 732 2.00 <NA> NA 20131216 126436 BAL BAL
#> 733 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 734 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 735 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 736 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 737 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 738 2.00 <NA> NA 20131216 126436 BAL BAL
#> 739 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 740 4.00 <NA> NA 20190207 126436 RUEK RUEK
#> 741 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 742 2.00 <NA> NA 20161115 126436 ARG ARG
#> 743 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 744 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 745 2.00 <NA> NA 20190228 126436 ARG ARG
#> 746 2.00 <NA> NA 20190228 126436 ARG ARG
#> 747 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 748 2.00 <NA> NA 20190208 126436 ARG ARG
#> 749 9.00 <NA> NA 20190208 126436 BAL BAL
#> 750 2.00 <NA> NA 20190208 126436 BAL BAL
#> 751 2.00 <NA> NA 20190208 126436 ARG ARG
#> 752 2.00 <NA> NA 20190208 126436 ARG ARG
#> 753 2.00 <NA> NA 20161115 126436 ARG ARG
#> 754 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 755 1.00 <NA> NA 20211203 126436 LAIZ LAIZ
#> 756 1.00 <NA> NA 20211203 126436 LAIZ LAIZ
#> 757 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 758 1.00 <NA> NA 20211203 126436 ARG ARG
#> 759 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 760 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 761 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 762 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 763 2.00 <NA> NA 20161115 126436 BAL BAL
#> 764 2.00 <NA> NA 20161115 126436 BAL BAL
#> 765 2.00 <NA> NA 20161115 126436 BAL BAL
#> 766 2.00 <NA> NA 20161115 126436 ATL ATL
#> 767 2.00 <NA> NA 20161115 126436 ARG ARG
#> 768 2.00 <NA> NA 20161115 126436 ARG ARG
#> 769 1.76 <NA> NA 20161115 126436 ARG ARG
#> 770 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 771 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 772 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 773 2.00 <NA> NA 20180423 126436 ATL ATL
#> 774 12.00 <NA> NA 20180423 126436 ATL ATL
#> 775 2.00 <NA> NA 20180423 126436 BAL BAL
#> 776 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 777 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 778 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 779 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 780 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 781 2.00 <NA> NA 20140219 126436 BAL BAL
#> 782 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 783 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 784 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 785 6.00 <NA> NA 20180423 126436 ATLD ATLD
#> 786 2.00 <NA> NA 20180507 126436 BAL BAL
#> 787 2.00 <NA> NA 20180507 126436 ARG ARG
#> 788 1.00 <NA> NA 20200115 126436 SOL2 SOL2
#> 789 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 790 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 791 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 792 2.00 <NA> NA 20140617 126436 BAL BAL
#> 793 6.00 <NA> NA 20140617 126436 ATLD ATLD
#> 794 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 795 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 796 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 797 3.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 798 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 799 2.00 <NA> NA 20211203 126436 SOL SOL
#> 800 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 801 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 802 2.00 <NA> NA 20140616 126436 SOL SOL
#> 803 2.00 <NA> NA 20140616 126436 BAL BAL
#> 804 1.00 <NA> NA 20140616 126436 AA36 AA36
#> 805 2.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 806 2.00 <NA> NA 20131112 126436 ARG ARG
#> 807 8.00 <NA> NA 20131112 126436 AA36 AA36
#> 808 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 809 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 810 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 811 1.00 <NA> NA 20211203 126436 SOL SOL
#> 812 1.00 <NA> NA 20211203 126436 ARG ARG
#> 813 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 814 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 815 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 816 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 817 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 818 2.00 <NA> NA 20131113 126436 ARG ARG
#> 819 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 820 2.00 <NA> NA 20180507 126436 BAL BAL
#> 821 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 822 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 823 2.00 <NA> NA 20131204 126436 BAL BAL
#> 824 2.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 825 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 826 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 827 2.60 <NA> NA 20161213 126436 ARG ARG
#> 828 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 829 2.00 <NA> NA 20161213 126436 ARG ARG
#> 830 2.00 <NA> NA 20161213 126436 ARG ARG
#> 831 2.00 <NA> NA 20161213 126436 BAL BAL
#> 832 2.00 <NA> NA 20161115 126436 ARG ARG
#> 833 2.00 <NA> NA 20161115 126436 ARG ARG
#> 834 2.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 835 2.00 <NA> NA 20131216 126436 BAL BALL
#> 836 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 837 2.00 <NA> NA 20131216 126436 ATL ATL
#> 838 2.00 <NA> NA 20131216 126436 ATL ATL
#> 839 2.00 <NA> NA 20131216 126436 BAL BAL
#> 840 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 841 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 842 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 843 2.00 <NA> NA 20160721 126436 BAL BAL
#> 844 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 845 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 846 2.00 <NA> NA 20190207 126436 SOL SOL
#> 847 2.00 <NA> NA 20190207 126436 SOL SOL
#> 848 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 849 2.00 <NA> NA 20190228 126436 SOL SOL
#> 850 2.00 <NA> NA 20190228 126436 ARG ARG
#> 851 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 852 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 853 2.00 <NA> NA 20190208 126436 BAL BAL
#> 854 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 855 2.00 <NA> NA 20190208 126436 ARG ARG
#> 856 2.00 <NA> NA 20161115 126436 ARG ARG
#> 857 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 858 6.00 <NA> NA 20140611 126436 BAL BAL
#> 859 2.00 <NA> NA 20140611 126436 ATLD ATLD
#> 860 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 861 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 862 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 863 2.00 <NA> NA 20211203 126436 ARG ARG
#> 864 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 865 2.00 <NA> NA 20161115 126436 BAL BAL
#> 866 2.00 <NA> NA 20161115 126436 BAL BAL
#> 867 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 868 2.00 <NA> NA 20161115 126436 ARG ARG
#> 869 4.00 <NA> NA 20161115 126436 ARG ARG
#> 870 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 871 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 872 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 873 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 874 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 875 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 876 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 877 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 878 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 879 2.00 <NA> NA 20140219 126436 BAL BAL
#> 880 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 881 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 882 2.00 <NA> NA 20131216 126436 ATL ATL
#> 883 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 884 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 885 2.00 <NA> NA 20131216 126436 BAL BAL
#> 886 2.00 <NA> NA 20140617 126436 SOL SOL
#> 887 2.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 888 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 889 2.00 <NA> NA 20140617 126436 BAL BAL
#> 890 2.00 <NA> NA 20140617 126436 ARG ARG
#> 891 2.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 892 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 893 2.00 <NA> NA 20140616 126436 SOL SOL
#> 894 2.00 <NA> NA 20140616 126436 ATL ATL
#> 895 2.00 <NA> NA 20140616 126436 BAL BAL
#> 896 2.00 <NA> NA 20140616 126436 BAL BAL
#> 897 2.00 <NA> NA 20140616 126436 ARG ARG
#> 898 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 899 1.00 <NA> NA 20211203 126436 SOL SOL
#> 900 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 901 1.00 <NA> NA 20211203 126436 SOL SOL
#> 902 1.00 <NA> NA 20211203 126436 SOL SOL
#> 903 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 904 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 905 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 906 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 907 1.00 <NA> NA 20211203 126436 SOL SOL
#> 908 1.00 <NA> NA 20211203 126436 SOL SOL
#> 909 1.00 <NA> NA 20211203 126436 SOL SOL
#> 910 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 911 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 912 2.00 <NA> NA 20131204 126436 SOL SOL
#> 913 2.00 <NA> NA 20131204 126436 ARG ARG
#> 914 2.00 <NA> NA 20131113 126436 ARG ARG
#> 915 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 916 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 917 2.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 918 2.00 <NA> NA 20161213 126436 BAL BAL
#> 919 4.00 <NA> NA 20161213 126436 BAL BAL
#> 920 2.00 <NA> NA 20161115 126436 ARG ARG
#> 921 1.00 <NA> NA 20131204 126436 SOL2 SOL2
#> 922 3.00 <NA> NA 20131204 126436 BAL BAL
#> 923 2.00 <NA> NA 20131204 126436 BAL BAL
#> 924 2.00 <NA> NA 20131204 126436 ATL ATL
#> 925 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 926 2.00 <NA> NA 20131216 126436 BAL BAL
#> 927 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 928 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 929 10.00 <NA> NA 20131216 126436 ATL ATL
#> 930 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 931 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 932 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 933 2.00 <NA> NA 20160721 126436 ARG ARG
#> 934 2.00 <NA> NA 20160721 126436 BAL BAL
#> 935 2.00 <NA> NA 20160721 126436 BAL BAL
#> 936 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 937 2.00 <NA> NA 20190228 126436 BAL BAL
#> 938 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 939 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 940 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 941 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 942 2.00 <NA> NA 20190207 126436 ARG ARG
#> 943 2.00 <NA> NA 20161115 126436 ARG ARG
#> 944 1.00 <NA> NA 20140611 126436 SOL2 SOL2
#> 945 2.00 <NA> NA 20140617 126436 BAL BAL
#> 946 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 947 2.00 <NA> NA 20190208 126436 SOL SOL
#> 948 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 949 2.00 <NA> NA 20190208 126436 BAL BAL
#> 950 2.00 <NA> NA 20190208 126436 ARG ARG
#> 951 2.00 <NA> NA 20190208 126436 ARG ARG
#> 952 2.00 <NA> NA 20161115 126436 ARG ARG
#> 953 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 954 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 955 2.00 <NA> NA 20161115 126436 ARG ARG
#> 956 2.00 <NA> NA 20161115 126436 ARG ARG
#> 957 2.00 <NA> NA 20211203 126436 SOL SOL
#> 958 1.00 <NA> NA 20211203 126436 ARG ARG
#> 959 1.00 <NA> NA 20211203 126436 ARG ARG
#> 960 1.00 <NA> NA 20211203 126436 ARG ARG
#> 961 1.00 <NA> NA 20211203 126436 ARG ARG
#> 962 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 963 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 964 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 965 3.00 <NA> NA 20180423 126436 ATL ATL
#> 966 16.00 <NA> NA 20180423 126436 ATL ATL
#> 967 2.00 <NA> NA 20180423 126436 ARG ARG
#> 968 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 969 2.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 970 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 971 3.00 <NA> NA 20180507 126436 ATLD ATLD
#> 972 13.00 <NA> NA 20180423 126436 ATLD ATLD
#> 973 3.00 <NA> NA 20180423 126436 ATLD ATLD
#> 974 1.00 <NA> NA 20180507 126436 DAR DAR
#> 975 2.00 <NA> NA 20180507 126436 BAL BAL
#> 976 4.00 <NA> NA 20180507 126436 BAL BAL
#> 977 4.00 <NA> NA 20180507 126436 BAL BAL
#> 978 2.00 <NA> NA 20180507 126436 BAL BAL
#> 979 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 980 2.00 <NA> NA 20131216 126436 DAR DAR
#> 981 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 982 2.00 <NA> NA 20131216 126436 BAL BAL
#> 983 2.00 <NA> NA 20131216 126436 BAL BAL
#> 984 2.00 <NA> NA 20160714 126436 ARG ARG
#> 985 2.00 <NA> NA 20160714 126436 ATL ATL
#> 986 2.00 <NA> NA 20160714 126436 BAL BAL
#> 987 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 988 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 989 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 990 4.00 <NA> NA 20140617 126436 ATLD ATLD
#> 991 6.00 <NA> NA 20180423 126436 BAL BAL
#> 992 8.00 <NA> NA 20180507 126436 BAL BAL
#> 993 2.00 <NA> NA 20160721 126436 ARG ARG
#> 994 2.00 <NA> NA 20160721 126436 ARG ARG
#> 995 2.00 <NA> NA 20160721 126436 BAL BAL
#> 996 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 997 2.00 <NA> NA 20140616 126436 SOL SOL
#> 998 2.00 <NA> NA 20140616 126436 SOL SOL
#> 999 1.00 <NA> NA 20140616 126436 AA36 AA36
#> 1000 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1001 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 1002 2.00 <NA> NA 20131108 126436 ARG ARG
#> 1003 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1004 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1005 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1006 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1007 3.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 1008 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1009 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1010 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1011 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1012 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1013 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1014 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1015 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1016 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1017 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1018 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1019 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1020 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1021 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1022 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1023 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1024 1.00 <NA> NA 20131204 126436 SOL2 SOL2
#> 1025 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1026 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1027 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 1028 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1029 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1030 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1031 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1032 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1033 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1034 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 1035 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1036 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1037 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1038 2.00 <NA> NA 20140611 126436 BAL BAL
#> 1039 2.00 <NA> NA 20190207 126436 SOL SOL
#> 1040 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1041 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1042 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1043 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1044 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1045 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1046 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1047 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1048 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1049 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1050 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1051 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1052 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1053 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1054 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1055 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1056 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1057 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1058 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1059 16.00 <NA> NA 20180423 126436 ATL ATL
#> 1060 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1061 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1062 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1063 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1064 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1065 2.00 <NA> NA 20180507 126436 ARG ARG
#> 1066 11.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1067 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1068 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1069 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1070 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1071 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1072 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1073 2.00 <NA> NA 20161115 126436 AA36 AA36
#> 1074 2.00 <NA> NA 20161115 126436 SOL SOL
#> 1075 2.00 <NA> NA 20140219 126436 DAR DAR
#> 1076 2.00 <NA> NA 20140219 126436 BAL BAL
#> 1077 3.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1078 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1079 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1080 2.00 <NA> NA 20200115 126436 BAL BAL
#> 1081 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1082 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1083 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1084 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1085 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1086 3.00 <NA> NA 20131111 126436 ARG ARG
#> 1087 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 1088 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1089 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 1090 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1091 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1092 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1093 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1094 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1095 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1096 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1097 3.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1098 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1099 2.00 <NA> NA 20131108 126436 ATL ATL
#> 1100 2.00 <NA> NA 20131108 126436 ATL ATL
#> 1101 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1102 3.00 <NA> NA 20131113 126436 ARG ARG
#> 1103 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 1104 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1105 2.00 <NA> NA 20140616 126436 SOL SOL
#> 1106 1.00 <NA> NA 20140616 126436 AA36 AA36
#> 1107 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1108 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1109 4.29 <NA> NA 20131113 126436 ARG ARG
#> 1110 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1111 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1112 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 1113 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1114 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1115 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1116 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1117 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1118 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1119 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1120 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1121 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1122 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1123 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1124 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1125 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1126 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1127 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1128 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1129 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1130 4.00 <NA> NA 20211203 126436 90MX 90MX
#> 1131 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 1132 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1133 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 1134 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1135 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 1136 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 1137 2.00 <NA> NA 20190228 126436 BAL BAL
#> 1138 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1139 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 1140 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1141 2.00 <NA> NA 20140611 126436 BAL BAL
#> 1142 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1143 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1144 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1145 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1146 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1147 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1148 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1149 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1150 2.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1151 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1152 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1153 2.00 <NA> NA 20190208 126436 BAL BAL
#> 1154 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1155 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1156 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1157 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1158 2.00 <NA> NA 20180423 126436 ATLD ATLD
#> 1159 1.00 <NA> NA 20180507 126436 SOL2 SOL2
#> 1160 4.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1161 5.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1162 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1163 2.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1164 4.00 <NA> NA 20180423 126436 BAL BAL
#> 1165 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1166 2.00 <NA> NA 20200115 126436 ARG ARG
#> 1167 2.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1168 2.00 <NA> NA 20140219 126436 BAL BAL
#> 1169 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1170 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1171 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 1172 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1173 1.76 <NA> NA 20161115 126436 ARG ARG
#> 1174 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1175 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1176 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1177 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1178 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1179 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1180 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1181 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1182 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1183 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1184 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 1185 2.00 <NA> NA 20160714 126436 ATL ATL
#> 1186 2.00 <NA> NA 20160714 126436 ARG ARG
#> 1187 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1188 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1189 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1190 1.00 <NA> NA 20180507 126436 SOL2 SOL2
#> 1191 2.00 <NA> NA 20160721 126436 ARG ARG
#> 1192 2.00 <NA> NA 20160721 126436 ATL ATL
#> 1193 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1194 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1195 2.00 <NA> NA 20180507 126436 ATL ATL
#> 1196 2.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1197 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1198 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1199 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1200 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1201 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1202 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1203 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1204 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1205 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1206 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1207 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 1208 1.00 <NA> NA 20131108 126436 SOL SOL
#> 1209 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1210 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1211 2.00 <NA> NA 20131108 126436 ATL ATL
#> 1212 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1213 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 1214 2.00 <NA> NA 20131113 126436 BAL BAL
#> 1215 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1216 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1217 2.00 <NA> NA 20131204 126436 SOL SOL
#> 1218 2.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 1219 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1220 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1221 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1222 2.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1223 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 1224 2.00 <NA> NA 20160721 126436 ARG ARG
#> 1225 2.00 <NA> NA 20160721 126436 BAL BAL
#> 1226 2.00 <NA> NA 20160721 126436 BAL BAL
#> 1227 2.00 <NA> NA 20160721 126436 BAL BAL
#> 1228 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1229 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1230 2.00 <NA> NA 20161213 126436 BAL BAL
#> 1231 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1232 2.00 <NA> NA 20161115 126436 SOL SOL
#> 1233 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1234 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1235 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1236 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1237 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1238 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1239 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1240 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1241 3.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1242 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1243 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1244 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1245 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1246 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1247 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1248 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1249 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1250 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1251 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1252 2.00 <NA> NA 20140611 126436 ATLD ATLD
#> 1253 2.00 <NA> NA 20140611 126436 ATLD ATLD
#> 1254 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1255 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1256 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 1257 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1258 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1259 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1260 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1261 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1262 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1263 6.00 <NA> NA 20180423 126436 ATLD ATLD
#> 1264 2.00 <NA> NA 20180423 126436 BAL BALL
#> 1265 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1266 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1267 4.00 <NA> NA 20180507 126436 BAL BAL
#> 1268 2.00 <NA> NA 20190207 126436 SOL SOL
#> 1269 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1270 1.00 <NA> NA 20190207 126436 BAL BAL
#> 1271 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1272 4.00 <NA> NA 20161115 126436 ARG ARG
#> 1273 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1274 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1275 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1276 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1277 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1278 3.00 <NA> NA 20180423 126436 ATL ATL
#> 1279 2.00 <NA> NA 20180423 126436 BAL BAL
#> 1280 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1281 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1282 2.00 <NA> NA 20180507 126436 ARG ARG
#> 1283 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1284 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1285 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1286 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1287 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1288 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1289 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1290 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1291 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1292 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1293 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1294 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1295 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1296 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1297 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1298 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1299 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1300 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1301 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1302 2.00 <NA> NA 20140219 126436 ATL ATL
#> 1303 2.00 <NA> NA 20140219 126436 ATL ATL
#> 1304 2.00 <NA> NA 20140219 126436 BAL BAL
#> 1305 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1306 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1307 4.00 <NA> NA 20161115 126436 BAL BAL
#> 1308 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1309 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1310 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1311 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1312 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 1313 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1314 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 1315 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 1316 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 1317 2.00 <NA> NA 20160714 126436 ATL ATL
#> 1318 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1319 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1320 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1321 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1322 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1323 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1324 2.00 <NA> NA 20180507 126436 ATL ATL
#> 1325 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1326 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1327 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1328 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1329 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1330 4.00 <NA> NA 20140617 126436 BAL BAL
#> 1331 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1332 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1333 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1334 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1335 2.00 <NA> NA 20131204 126436 BAL BAL
#> 1336 3.00 <NA> NA 20131204 126436 ATL ATL
#> 1337 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1338 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1339 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1340 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1341 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1342 3.00 <NA> NA 20131216 126436 ATL ATL
#> 1343 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 1344 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1345 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 1346 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1347 2.00 <NA> NA 20131204 126436 BAL BAL
#> 1348 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1349 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1350 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1351 2.00 <NA> NA 20140616 126436 ARG ARG
#> 1352 2.00 <NA> NA 20140616 126436 BAL BAL
#> 1353 1.00 <NA> NA 20140616 126436 AA36 AA36
#> 1354 2.00 <NA> NA 20140616 126436 ARG ARG
#> 1355 4.00 <NA> NA 20131112 126436 ARG ARG
#> 1356 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1357 2.00 <NA> NA 20161213 126436 SOL SOL
#> 1358 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1359 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1360 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1361 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1362 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1363 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1364 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1365 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1366 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1367 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1368 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1369 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1370 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1371 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1372 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1373 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1374 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1375 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1376 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1377 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1378 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1379 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1380 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1381 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1382 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1383 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1384 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1385 1.00 <NA> NA 20131112 126436 DAN2 DAN2
#> 1386 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1387 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1388 1.00 <NA> NA 20180507 126436 DAR DAR
#> 1389 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1390 4.00 <NA> NA 20180507 126436 BAL BAL
#> 1391 4.00 <NA> NA 20180507 126436 BAL BAL
#> 1392 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1393 2.00 <NA> NA 20180507 126436 ARG ARG
#> 1394 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1395 2.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1396 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1397 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1398 3.00 <NA> NA 20180423 126436 ATL ATL
#> 1399 2.00 <NA> NA 20180423 126436 ATL ATL
#> 1400 6.00 <NA> NA 20180423 126436 ATL ATL
#> 1401 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1402 3.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1403 2.00 <NA> NA 20180507 126436 ARG ARG
#> 1404 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1405 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1406 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1407 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1408 4.00 <NA> NA 20140219 126436 ATL ATL
#> 1409 2.00 <NA> NA 20140219 126436 BAL BAL
#> 1410 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1411 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1412 1.00 <NA> 1 20210503 126436 SOL2 SOL2
#> 1413 2.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1414 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1415 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1416 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1417 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1418 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1419 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1420 3.00 <NA> NA 20161115 126436 SOL SOL
#> 1421 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1422 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1423 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1424 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1425 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1426 9.00 <NA> NA 20190208 126436 SOL SOL
#> 1427 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1428 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1429 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1430 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1431 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1432 4.00 <NA> NA 20190208 126436 ARG ARG
#> 1433 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1434 2.40 <NA> NA 20161115 126436 ARG ARG
#> 1435 1.00 <NA> 1 20210319 126436 SOL2 SOL2
#> 1436 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1437 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1438 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1439 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1440 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1441 2.00 <NA> NA 20160714 126436 SOL SOL
#> 1442 2.14 <NA> NA 20160714 126436 ARG ARG
#> 1443 3.00 <NA> NA 20160714 126436 ATL ATL
#> 1444 2.00 <NA> NA 20160714 126436 ARG ARG
#> 1445 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1446 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1447 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1448 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1449 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1450 2.00 <NA> NA 20180507 126436 ATL ATL
#> 1451 1.00 <NA> NA 20131204 126436 DAN2 DAN2
#> 1452 1.00 <NA> NA 20131204 126436 SOL2 SOL2
#> 1453 2.00 <NA> NA 20131204 126436 ATL ATL
#> 1454 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1455 2.00 <NA> NA 20131216 126436 ATLD ATLD
#> 1456 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1457 2.00 <NA> NA 20140617 126436 SOL SOL
#> 1458 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1459 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1460 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1461 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1462 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1463 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1464 2.00 <NA> NA 20131112 126436 SOL SOL
#> 1465 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1466 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1467 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1468 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1469 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1470 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1471 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1472 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1473 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1474 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 1475 2.00 <NA> NA 20131204 126436 BAL BAL
#> 1476 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1477 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1478 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1479 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1480 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1481 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1482 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1483 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1484 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1485 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1486 4.00 <NA> NA 20211203 126436 SOL SOL
#> 1487 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1488 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1489 2.00 <NA> NA 20211203 126436 ARG ARG
#> 1490 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1491 2.00 <NA> NA 20211203 126436 ARG ARG
#> 1492 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1493 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1494 1.00 <NA> NA 20140611 126436 SOL2 SOL2
#> 1495 3.00 <NA> NA 20140611 126436 BAL BAL
#> 1496 2.00 <NA> NA 20140611 126436 BAL BAL
#> 1497 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1498 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1499 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1500 1.00 <NA> NA 20180423 126436 SOL2 SOL2
#> 1501 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1502 2.00 <NA> NA 20180423 126436 BAL BAL
#> 1503 4.00 <NA> NA 20180423 126436 ARG ARG
#> 1504 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1505 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1506 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1507 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1508 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1509 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1510 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1511 4.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1512 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1513 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1514 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1515 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1516 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1517 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1518 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1519 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1520 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1521 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1522 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1523 2.00 <NA> NA 20180423 126436 ATL ATL
#> 1524 4.00 <NA> NA 20180423 126436 BAL BAL
#> 1525 40.00 <NA> NA 20180423 126436 BAL BALL
#> 1526 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1527 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1528 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1529 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1530 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1531 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1532 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1533 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1534 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1535 1.00 <NA> NA 20140219 126436 SOL2 SOL2
#> 1536 2.00 <NA> NA 20140219 126436 ATL ATL
#> 1537 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1538 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1539 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1540 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1541 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1542 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1543 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1544 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1545 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1546 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1547 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1548 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1549 2.00 <NA> NA 20190208 126436 BAL BAL
#> 1550 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1551 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1552 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1553 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1554 9.00 <NA> NA 20190207 126436 SOL SOL
#> 1555 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1556 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1557 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1558 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1559 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1560 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1561 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1562 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1563 10.00 <NA> NA 20190607 126436 BAL BAL
#> 1564 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1565 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1566 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1567 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1568 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1569 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1570 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1571 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1572 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 1573 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1574 6.00 <NA> NA 20180423 126436 BAL BAL
#> 1575 2.00 <NA> NA 20160714 126436 SOL SOL
#> 1576 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 1577 2.00 <NA> NA 20160714 126436 BAL BAL
#> 1578 2.00 <NA> NA 20160714 126436 BAL BAL
#> 1579 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1580 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1581 2.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1582 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1583 2.00 <NA> NA 20160721 126436 AA36 AA36
#> 1584 2.00 <NA> NA 20160721 126436 BAL BAL
#> 1585 2.00 <NA> NA 20160721 126436 ARG ARG
#> 1586 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1587 2.00 <NA> NA 20131204 126436 ATL ATL
#> 1588 2.00 <NA> NA 20131204 126436 ATL ATL
#> 1589 4.00 <NA> NA 20131216 126436 BAL BAL
#> 1590 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1591 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1592 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1593 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1594 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1595 4.00 <NA> NA 20131111 126436 SOL SOL
#> 1596 2.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1597 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1598 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1599 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1600 8.00 <NA> NA 20131216 126436 ATL ATL
#> 1601 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1602 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1603 4.00 <NA> NA 20131216 126436 BAL BAL
#> 1604 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1605 2.00 <NA> NA 20160721 126436 ARG ARG
#> 1606 2.00 <NA> NA 20160721 126436 BAL BAL
#> 1607 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1608 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1609 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1610 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1611 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1612 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1613 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1614 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1615 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1616 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1617 1.00 <NA> NA 20131108 126436 DAN2 DAN2
#> 1618 2.00 <NA> NA 20131108 126436 ARG ARG
#> 1619 2.00 <NA> NA 20131108 126436 ARG ARG
#> 1620 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1621 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1622 2.00 <NA> NA 20131113 126436 ATLD ATLD
#> 1623 4.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 1624 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1625 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1626 2.00 <NA> NA 20140616 126436 ATL ATL
#> 1627 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1628 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1629 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1630 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1631 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1632 4.00 <NA> NA 20161115 126436 ARG ARG
#> 1633 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1634 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1635 2.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1636 4.00 <NA> NA 20140611 126436 ATLD ATLD
#> 1637 5.00 <NA> NA 20140611 126436 BAL BAL
#> 1638 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1639 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1640 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1641 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1642 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1643 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1644 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1645 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1646 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1647 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1648 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1649 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1650 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1651 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1652 2.00 <NA> NA 20180423 126436 ARG ARG
#> 1653 2.00 <NA> NA 20180423 126436 ARG ARG
#> 1654 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1655 4.00 <NA> NA 20180507 126436 BAL BALL
#> 1656 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1657 2.00 <NA> NA 20200115 126436 ATLD ATLD
#> 1658 2.00 <NA> NA 20200115 126436 BAL BAL
#> 1659 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1660 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1661 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1662 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1663 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1664 2.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1665 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1666 2.00 <NA> NA 20180423 126436 ATL ATL
#> 1667 16.00 <NA> NA 20180423 126436 ATL ATL
#> 1668 3.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1669 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1670 2.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1671 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1672 2.00 <NA> NA 20140219 126436 ARG ARG
#> 1673 2.00 <NA> NA 20140219 126436 ATL ATL
#> 1674 12.00 <NA> NA 20140219 126436 ATL ATL
#> 1675 3.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1676 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1677 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1678 2.00 <NA> NA 20190228 126436 SOL SOL
#> 1679 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 1680 1.00 <NA> NA 20190228 126436 DAN2 DAN2
#> 1681 2.00 <NA> NA 20190228 126436 SOL SOL
#> 1682 2.00 <NA> NA 20190228 126436 ATL ATL
#> 1683 2.00 <NA> NA 20190228 126436 BAL BAL
#> 1684 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1685 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1686 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1687 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1688 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1689 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1690 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1691 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1692 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1693 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1694 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1695 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1696 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1697 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1698 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1699 1.00 <NA> NA 20190607 126436 DAN2 DAN2
#> 1700 2.00 <NA> NA 20190208 126436 SOL SOL
#> 1701 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1702 4.00 <NA> NA 20190208 126436 SOL SOL
#> 1703 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1704 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1705 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1706 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1707 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1708 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1709 4.00 <NA> NA 20190208 126436 ARG ARG
#> 1710 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1711 9.00 <NA> NA 20190207 126436 SOL SOL
#> 1712 2.00 <NA> NA 20190207 126436 SOL SOL
#> 1713 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1714 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1715 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1716 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1717 6.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1718 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1719 4.00 <NA> NA 20161115 126436 SOL SOL
#> 1720 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1721 4.00 <NA> NA 20161115 126436 ARG ARG
#> 1722 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1723 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1724 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1725 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1726 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1727 2.00 <NA> NA 20161115 126436 ATL ATL
#> 1728 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1729 4.00 <NA> NA 20161115 126436 ARG ARG
#> 1730 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1731 2.00 <NA> NA 20160714 126436 SOL SOL
#> 1732 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 1733 1.00 <NA> NA 20160714 126436 DAN2 DAN2
#> 1734 2.00 <NA> NA 20160714 126436 ATL ATL
#> 1735 2.00 <NA> NA 20160714 126436 ARG ARG
#> 1736 2.00 <NA> NA 20160714 126436 ARG ARG
#> 1737 1.71 <NA> NA 20160714 126436 ARG ARG
#> 1738 2.00 <NA> NA 20131113 126436 SOL SOL
#> 1739 2.00 <NA> NA 20131113 126436 ARG ARG
#> 1740 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1741 2.00 <NA> NA 20131204 126436 BAL BAL
#> 1742 2.00 <NA> NA 20131204 126436 ATL ATL
#> 1743 2.00 <NA> NA 20131204 126436 ATL ATL
#> 1744 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1745 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1746 4.00 <NA> NA 20160721 126436 ATL ATL
#> 1747 2.00 <NA> NA 20160721 126436 ATL ATL
#> 1748 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1749 2.00 <NA> NA 20180507 126436 AA36 AA36
#> 1750 2.00 <NA> NA 20180507 126436 BAL BAL
#> 1751 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1752 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1753 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1754 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1755 1.00 <NA> NA 20131216 126436 SOL2 SOL2
#> 1756 3.00 <NA> NA 20131216 126436 ATL ATL
#> 1757 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1758 2.00 <NA> NA 20131216 126436 ATL ATL
#> 1759 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1760 1.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1761 2.00 <NA> NA 20160721 126436 DAN2 DAN2
#> 1762 1.00 <NA> NA 20160721 126436 SOL2 SOL2
#> 1763 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1764 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1765 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1766 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1767 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1768 6.00 <NA> NA 20131111 126436 ARG ARG
#> 1769 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1770 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1771 1.00 <NA> NA 20140617 126436 DAN2 DAN2
#> 1772 2.00 <NA> NA 20140617 126436 ATLD ATLD
#> 1773 4.00 <NA> NA 20140617 126436 BAL BAL
#> 1774 4.00 <NA> NA 20140617 126436 BAL BAL
#> 1775 2.00 <NA> NA 20140617 126436 BAL BAL
#> 1776 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1777 2.00 <NA> NA 20140617 126436 ARG ARG
#> 1778 4.00 <NA> NA 20131112 126436 ARG ARG
#> 1779 2.00 <NA> NA 20131204 126436 SOL SOL
#> 1780 2.00 <NA> NA 20131204 126436 ARG ARG
#> 1781 5.00 <NA> NA 20131204 126436 RUS6 RUS6
#> 1782 2.00 <NA> NA 20131113 126436 SOL SOL
#> 1783 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1784 3.00 <NA> NA 20131113 126436 SOL SOL
#> 1785 1.00 <NA> NA 20131113 126436 DAN2 DAN2
#> 1786 1.00 <NA> NA 20140616 126436 DAN2 DAN2
#> 1787 2.00 <NA> NA 20140616 126436 ATL ATL
#> 1788 2.00 <NA> NA 20140616 126436 BAL BAL
#> 1789 2.00 <NA> NA 20140616 126436 ARG ARG
#> 1790 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1791 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 1792 2.00 <NA> NA 20131112 126436 ARG ARG
#> 1793 1.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1794 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1795 2.00 <NA> NA 20161213 126436 DAN2 DAN2
#> 1796 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1797 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1798 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1799 2.00 <NA> NA 20161213 126436 BAL BAL
#> 1800 2.00 <NA> NA 20161213 126436 ARG ARG
#> 1801 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1802 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1803 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1804 1.00 <NA> NA 20140611 126436 DAN2 DAN2
#> 1805 1.00 <NA> NA 20140611 126436 SOL2 SOL2
#> 1806 11.00 <NA> NA 20140611 126436 BAL BAL
#> 1807 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1808 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1809 2.00 <NA> NA 20180423 126436 ARG ARG
#> 1810 1.00 <NA> NA 20180507 126436 SOL2 SOL2
#> 1811 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1812 4.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1813 2.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1814 6.28 <NA> NA 20180507 126436 ARG ARG
#> 1815 4.00 <NA> NA 20180507 126436 BAL BALL
#> 1816 4.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1817 5.00 <NA> NA 20180507 126436 ATLD ATLD
#> 1818 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1819 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1820 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1821 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1822 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1823 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1824 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1825 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1826 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1827 3.00 <NA> NA 20211203 126436 SOL SOL
#> 1828 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1829 1.00 <NA> NA 20211203 126436 ARG ARG
#> 1830 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1831 1.00 <NA> NA 20200115 126436 DAN2 DAN2
#> 1832 2.00 <NA> NA 20200115 126436 BAL BAL
#> 1833 2.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1834 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1835 2.00 <NA> NA 20131216 126436 BAL BAL
#> 1836 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1837 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1838 1.00 <NA> NA 20140219 126436 DAN2 DAN2
#> 1839 1.00 <NA> NA 20131216 126436 DAN2 DAN2
#> 1840 2.00 <NA> NA 20131216 126436 ARG ARG
#> 1841 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1842 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1843 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1844 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1845 2.00 <NA> NA 20180423 126436 ATL ATL
#> 1846 16.00 <NA> NA 20180423 126436 ATL ATL
#> 1847 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1848 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1849 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1850 2.00 <NA> NA 20190228 126436 SOL SOL
#> 1851 2.00 <NA> NA 20190228 126436 ARG ARG
#> 1852 2.00 <NA> NA 20131112 126436 AA36 AA36
#> 1853 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1854 2.00 <NA> NA 20180423 126436 BAL BAL
#> 1855 1.00 <NA> NA 20180423 126436 DAN2 DAN2
#> 1856 1.00 <NA> NA 20190607 126436 SOL2 SOL2
#> 1857 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1858 2.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1859 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1860 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1861 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1862 3.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1863 3.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1864 1.00 <NA> NA 20211203 126436 DAN2 DAN2
#> 1865 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1866 2.00 <NA> NA 20211203 126436 SOL SOL
#> 1867 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1868 3.00 <NA> NA 20211203 126436 SOL SOL
#> 1869 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1870 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1871 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1872 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1873 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1874 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1875 1.00 <NA> NA 20211203 126436 SOL SOL
#> 1876 4.00 <NA> NA 20211203 126436 90MX 90MX
#> 1877 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1878 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 1879 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1880 2.00 <NA> NA 20211203 126436 AA36 AA36
#> 1881 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 1882 1.00 <NA> NA 20211203 126436 90MX 90MX
#> 1883 2.00 <NA> NA 20211203 126436 90MX 90MX
#> 1884 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1885 1.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1886 2.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1887 2.00 <NA> NA 20190208 126436 DAN2 DAN2
#> 1888 2.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1889 3.00 <NA> NA 20190208 126436 RUEK RUEK
#> 1890 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1891 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1892 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1893 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1894 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1895 2.00 <NA> NA 20190208 126436 ARG ARG
#> 1896 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1897 1.00 <NA> NA 20180507 126436 DAN2 DAN2
#> 1898 1.00 <NA> NA 20190207 126436 DAN2 DAN2
#> 1899 9.00 <NA> NA 20190207 126436 SOL SOL
#> 1900 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1901 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1902 1.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1903 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1904 2.00 <NA> NA 20190207 126436 ARG ARG
#> 1905 2.00 <NA> NA 20190207 126436 RUEK RUEK
#> 1906 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1907 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1908 4.00 <NA> NA 20161115 126436 ARG ARG
#> 1909 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1910 1.00 <NA> NA 20161115 126436 DAN2 DAN2
#> 1911 2.00 <NA> NA 20161115 126436 SOL SOL
#> 1912 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1913 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1914 2.00 <NA> NA 20161115 126436 BAL BAL
#> 1915 2.00 <NA> NA 20161115 126436 ATL ATL
#> 1916 2.00 <NA> NA 20161115 126436 ATL ATL
#> 1917 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1918 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1919 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1920 1.00 <NA> NA 20161115 126436 AA36 AA36
#> 1921 2.00 <NA> NA 20161115 126436 ARG ARG
#> 1922 1.76 <NA> NA 20161115 126436 ARG ARG
#> 1923 2.00 <NA> NA 20161115 126436 ARG ARG
#> IDx sub_div Rect HaulVal StdSpecRecCode
#> 1 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 2 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 3 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 4 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 5 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 6 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 7 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 8 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 9 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 10 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 11 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 12 1996.1.DEN.26D4.GRT.45.25 26 41H0 V 1
#> 13 1993.1.SWE.77AR.FOT.80.32 25 39G5 V 1
#> 14 1998.1.DEN.26D4.GRT.83.40 25 38G5 V 1
#> 15 1994.1.DEN.26D4.GRT.43.22 26 41H0 V 1
#> 16 1996.1.DEN.26D4.GRT.9.5 25 38G5 V 1
#> 17 1998.1.SWE.77AR.FOT.191.3 25 40G5 V 1
#> 18 1993.1.GFR.06S1.H20.46.20 24 39G4 V 1
#> 19 2003.1.DEN.26D4.TVL.71.36 25 39G5 V 1
#> 20 1991.1.LAT.90MX.LBT.000001.19 26 40H0 V 1
#> 21 1994.1.DEN.26D4.GRT.117.50 25 38G5 V 1
#> 22 1996.1.DEN.26D4.GRT.75.40 25 39G6 V 1
#> 23 2000.4.SWE.77AR.GOV.584.18 25 40G5 V 1
#> 24 2002.4.DEN.26D4.TVL.10.4 24 39G4 V 1
#> 25 1998.1.DEN.26D4.GRT.136.64 26 39G8 V 1
#> 26 1991.1.GFR.06S1.CHP.26073.50 26 39G8 V 1
#> 27 2002.4.SWE.77AR.TVL.573.11 25 41G7 V 1
#> 28 2000.1.SWE.77AR.GOV.220.21 24 39G3 V 1
#> 29 2000.1.SWE.77AR.GOV.237.34 25 40G5 V 1
#> 30 1991.1.DEN.26D4.GRT.106.57 25 39G7 V 1
#> 31 1996.1.DEN.26D4.GRT.111.47 25 39G5 V 1
#> 32 1996.4.SWE.77AR.FOT.231.26 28 43G8 V 1
#> 33 1995.4.SWE.77AR.FOT.247.2 25 40G5 V 1
#> 34 1999.4.SWE.77AR.GOV.652.17 25 40G5 V 1
#> 35 1998.1.SWE.77AR.FOT.207.15 25 40G7 V 1
#> 36 1993.1.DEN.26D4.GRT.162.72 25 38G5 V 1
#> 37 1996.1.DEN.26D4.GRT.53.30 26 41G9 V 1
#> 38 2006.1.RUS.RUJB.TVL.NA.13 26 39H0 V 1
#> 39 1995.1.DEN.26D4.GRT.57.23 26 41G9 V 1
#> 40 2008.1.GFR.06SL.TVS.24316.41 24 39G4 V 1
#> 41 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 42 1991.1.GFR.06S1.CHP.26073.50 26 39G8 V 1
#> 43 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 44 1998.1.SWE.77AR.FOT.222.26 28 43H0 V 1
#> 45 1994.1.GFR.06S1.H20.44.24 24 39G3 V 1
#> 46 2005.1.DEN.26D4.TVL.95.66 25 39G5 V 1
#> 47 1993.1.SWE.77AR.FOT.58.10 25 41G7 V 1
#> 48 2001.1.DEN.26D4.TVL.6.3 24 39G3 V 1
#> 49 1991.1.LAT.90MX.LBT.000001.12 26 39H0 V 1
#> 50 1993.1.DEN.26D4.GRT.17.9 24 39G4 V 1
#> 51 1993.1.LAT.LAIZ.LBT.000001.6 26 40H0 V 1
#> 52 1993.4.SWE.77AR.FOT.252.21 25 41G7 V 1
#> 53 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 54 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 55 1998.1.RUS.RUJB.HAK.NA.33 26 40G9 V 1
#> 56 2009.1.DEN.26D4.TVL.19.17 24 39G4 V 1
#> 57 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 58 2000.4.DEN.26D4.TVL.94.46 25 39G6 V 1
#> 59 1996.1.RUS.RUEK.DT.NA.13 26 39G8 V 1
#> 60 1995.1.DEN.26D4.GRT.33.14 26 41G8 V 1
#> 61 2010.1.DEN.26D4.TVL.100.1 25 39G6 V 1
#> 62 2000.1.DEN.26D4.GRT.16.8 25 40G5 V 1
#> 63 1996.1.DEN.26D4.GRT.66.36 25 39G7 V 1
#> 64 1996.1.SWE.77AR.FOT.74.23 25 40G6 V 1
#> 65 2004.1.POL.67BC.TVL.1.1 26 38G8 V 3
#> 66 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 67 1998.1.SWE.77AR.FOT.199.8 24 39G3 V 1
#> 68 1995.1.DEN.26D4.GRT.123.46 25 40G6 V 1
#> 69 2010.1.RUS.RUNT.TVL.60.17 26 39G8 V 1
#> 70 2009.1.SWE.77AR.TVL.267.52 25 40G4 V 1
#> 71 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 72 1994.4.GFR.06S1.H20.25.72 24 38G3 V 1
#> 73 1994.4.SWE.77AR.FOT.287.32 25 40G6 V 1
#> 74 2000.4.SWE.77AR.GOV.594.27 25 40G7 V 1
#> 75 2004.1.POL.67BC.TVL.2.2 26 39G8 V 3
#> 76 1998.1.RUS.RUJB.HAK.NA.37 26 40H0 V 1
#> 77 1995.1.DEN.26D4.GRT.11.3 25 39G7 V 1
#> 78 1994.1.GFR.06S1.H20.73.34 25 40G4 V 1
#> 79 1996.1.DEN.26D4.GRT.51.29 26 41G9 V 1
#> 80 1996.1.SWE.77AR.FOT.95.44 27 43G7 V 1
#> 81 2011.1.POL.67BC.TVL.26211.3 26 38G9 V 1
#> 82 1997.1.DEN.26D4.GRT.18.7 25 40G6 V 1
#> 83 1997.4.SWE.77AR.FOT.756.26 26 41G8 V 1
#> 84 1991.1.LAT.90MX.LBT.000001.11 26 41H0 V 1
#> 85 2010.1.RUS.RUNT.TVL.60.23 26 38G9 V 1
#> 86 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 87 1995.1.RUS.RUEK.DT.NA.19 26 38G9 V 1
#> 88 1994.1.DEN.26D4.GRT.63.32 26 39G8 V 1
#> 89 1994.1.POL.67BC.P20.Mar.18 26 38G8 V 1
#> 90 1996.1.DEN.26D4.GRT.46.26 26 41G9 V 1
#> 91 1999.1.RUS.RUNT.HAK.NA.5 26 38G9 V 1
#> 92 1993.1.GFR.06S1.H20.48.22 24 39G4 V 1
#> 93 2001.1.GFR.06S1.TVS.902.34 24 39G4 V 3
#> 94 2009.4.DEN.26D4.TVL.179.16 25 38G6 V 1
#> 95 2006.4.DEN.26D4.TVL.7.32 25 38G5 V 1
#> 96 2003.4.RUS.RUJB.TVL.NA.60 26 39H0 V 1
#> 97 1992.1.DEN.26D4.GRT.79.55 26 39G8 V 1
#> 98 2011.1.RUS.RUJB.TVL.56.40 26 39G9 V 1
#> 99 2011.4.DEN.26D4.TVL.39.42 25 40G4 V 1
#> 100 1996.1.GFR.06S1.H20.47.51 24 39G4 V 1
#> 101 1996.4.SWE.77AR.FOT.227.22 26 40G9 V 1
#> 102 1996.4.GFR.06S1.H20.25.68 24 38G3 V 1
#> 103 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 104 1991.1.GFR.06S1.CHP.26073.50 26 39G8 V 1
#> 105 1999.1.POL.67BC.P20.02Feb.10 26 38G8 V 1
#> 106 1999.4.LAT.AA36.LBT.2.9 26 41H0 V 1
#> 107 1998.1.SWE.77AR.FOT.206.14 25 40G7 V 1
#> 108 1995.1.SWE.77AR.GOV.75.23 25 41G7 V 1
#> 109 2006.1.SWE.77AR.TVL.223.30 25 40G4 V 1
#> 110 2001.1.RUS.RUNT.TVL.NA.10 26 39G9 V 1
#> 111 2008.4.POL.67BC.TVL.26014.21 26 37G9 V 3
#> 112 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 113 2008.4.RUS.RUJB.TVL.51.26 26 38G9 V 1
#> 114 1994.1.DEN.26D4.GRT.118.51 25 38G6 V 1
#> 115 1992.1.GFR.06S1.CHP.2810.36 28 42H0 V 1
#> 116 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 117 2000.4.SWE.77AR.GOV.584.18 25 40G5 V 1
#> 118 1996.1.DEN.26D4.GRT.36.20 28 44G9 V 1
#> 119 1998.1.GFR.06S1.H20.66.69 25 41G7 V 1
#> 120 1998.1.SWE.77AR.FOT.249.45 25 40G6 V 1
#> 121 1999.4.DEN.26D4.TVL.100019.12 25 39G7 V 1
#> 122 1991.1.POL.AA36.P20.03Mar.2 26 38G9 V 1
#> 123 2009.1.DEN.26D4.TVL.179.15 25 38G5 V 1
#> 124 2006.4.POL.67BC.TVL.25027.7 25 39G7 V 3
#> 125 1994.1.DEN.26D4.GRT.52.26 26 41G9 V 1
#> 126 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 127 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 128 2000.1.RUS.RUNT.HAK.NA.12 26 39H0 V 1
#> 129 2000.4.DEN.26D4.GRT.75.38 25 40G5 V 1
#> 130 2004.1.GFR.06S1.TVS.902.34 24 39G4 V 1
#> 131 1996.1.DEN.26D4.GRT.30.16 26 41G8 V 1
#> 132 2010.1.DEN.26D4.TVL.98.48 25 39G6 V 1
#> 133 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 134 1999.1.GFR.06S1.H20.65.119 25 37G5 V 1
#> 135 1999.1.POL.67BC.P20.03Mar.54 25 39G7 V 1
#> 136 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 137 1991.1.GFR.06S1.CHP.25225.78 25 38G5 V 1
#> 138 2001.1.DEN.26D4.TVL.56.27 25 39G6 V 1
#> 139 1993.1.POL.AA36.P20.02Feb.28 26 38G9 V 1
#> 140 1995.1.DEN.26D4.GRT.134.49 25 39G6 V 1
#> 141 1995.4.SWE.77AR.FOT.254.9 28 43G8 V 1
#> 142 2003.1.DEN.26D4.TVL.77.39 25 39G5 V 1
#> 143 2004.4.POL.67BC.TVL.NA.6 26 39G8 V 3
#> 144 2000.1.RUS.RUNT.HAK.NA.18 26 39G9 V 1
#> 145 2000.1.SWE.77AR.FOT.270.47 27 42G7 V 1
#> 146 2000.4.DEN.26D4.TVL.89.45 26 41H0 V 1
#> 147 1992.1.GFR.06S1.CHP.2504.46 25 39G5 V 1
#> 148 2010.4.DEN.26D4.TVL.166.16 25 38G5 V 1
#> 149 1996.1.DEN.26D4.GRT.62.34 26 40G9 V 1
#> 150 1996.1.RUS.RUEK.DT.NA.7 26 38G9 V 1
#> 151 1997.1.DEN.26D4.GRT.11.4 25 39G6 V 1
#> 152 1997.4.SWE.77AR.FOT.746.17 25 41G7 V 1
#> 153 1997.4.SWE.77AR.FOT.745.16 25 41G7 V 1
#> 154 1998.1.RUS.RUJB.HAK.NA.34 26 40G9 V 1
#> 155 1998.1.POL.67BC.P20.03Mar.63 25 39G7 V 1
#> 156 1998.1.RUS.RUJB.HAK.NA.37 26 40H0 V 1
#> 157 1998.4.SWE.77AR.FOT.738.35 27 42G7 V 1
#> 158 1998.4.SWE.77AR.FOT.715.17 25 40G5 V 1
#> 159 2009.1.DEN.26D4.TVL.266.37 25 39G6 V 1
#> 160 1999.1.GFR.06S1.H20.44.69 24 39G3 V 1
#> 161 1999.1.POL.67BC.P20.03Mar.69 26 37G9 V 1
#> 162 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 163 1991.1.POL.AA36.P20.01Jan.24 26 38G9 V 3
#> 164 1995.1.RUS.RUEK.DT.NA.44 26 40H0 V 1
#> 165 1995.1.SWE.77AR.GOV.94.42 27 43G7 V 1
#> 166 2003.1.GFR.06S1.TVS.2024.27 24 39G3 V 1
#> 167 1994.1.GFR.06S1.H20.44.24 24 39G3 V 1
#> 168 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 169 2004.1.GFR.06S1.TVS.17.32 24 39G4 V 1
#> 170 2000.1.DEN.26D4.GRT.64.31 26 41H0 V 1
#> 171 2000.4.DEN.26D4.TVL.87.44 26 39G8 V 1
#> 172 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 173 2010.1.GFR.06SL.TVS.24237.31 24 39G4 V 1
#> 174 1992.1.DEN.26D4.GRT.9.6 24 38G4 V 1
#> 175 1996.1.SWE.77AR.FOT.90.39 28 43G8 V 1
#> 176 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> 177 1999.4.LAT.AA36.LBT.2.8 26 41H0 V 1
#> 178 1995.1.DEN.26D4.GRT.21.8 25 41G7 V 1
#> 179 1995.1.SWE.77AR.GOV.95.43 27 43G6 V 1
#> 180 1995.1.RUS.RUEK.DT.NA.4 26 40G9 V 1
#> 181 1995.4.SWE.77AR.FOT.250.5 26 40G8 V 1
#> 182 1991.1.DEN.26D4.GRT.36.24 25 41G7 V 1
#> 183 1991.1.GFR.06S1.CHP.26071.48 26 38G8 V 1
#> 184 1993.1.GFR.06S1.H20.28.24 24 38G4 V 1
#> 185 1993.1.SWE.77AR.FOT.60.12 27 42G6 V 1
#> 186 2002.1.DEN.26D4.TVL.133.55 25 39G6 V 1
#> 187 2002.4.DEN.26D4.TVL.85.39 26 39H0 V 1
#> 188 1994.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 189 2010.4.SWE.77AR.TVL.670.2 25 40G4 V 1
#> 190 2000.1.DEN.26D4.GRT.26.13 25 40G7 V 1
#> 191 2000.1.SWE.77AR.GOV.220.21 24 39G3 V 1
#> 192 1996.1.DEN.26D4.GRT.32.18 26 41G8 V 1
#> 193 1996.1.DEN.26D4.GRT.50.28 26 41G9 V 1
#> 194 1992.1.GFR.06S1.CHP.2517.17 25 39G6 V 1
#> 195 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 196 1992.4.GFR.06S1.H20.28.38 24 38G4 V 1
#> 197 1997.1.DEN.26D4.GRT.11.4 25 39G6 V 1
#> 198 1997.1.SWE.77AR.FOT.185.9 24 39G4 V 1
#> 199 1997.4.SWE.77AR.FOT.746.17 25 41G7 V 1
#> 200 2005.1.GFR.06SL.TVS.24001.16 24 37G2 V 1
#> 201 2005.1.DEN.26D4.TVL.108.10 25 39G6 V 1
#> 202 2005.4.DEN.26D4.TVL.22.10 26 40G8 V 1
#> 203 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 204 1998.1.POL.67BC.P20.03Mar.55 25 38G5 V 1
#> 205 1998.1.SWE.77AR.FOT.230.31 28 43G9 V 1
#> 206 1998.4.SWE.77AR.FOT.718.20 25 40G7 V 1
#> 207 1998.4.SWE.77AR.FOT.720.22 25 41G7 V 1
#> 208 1999.1.DEN.26D4.GRT.44.20 25 38G5 V 1
#> 209 1999.1.POL.67BC.P20.02Feb.14 26 38G8 V 1
#> 210 1995.1.LAT.RUEK.DT.000001.23 26 41H0 V 1
#> 211 1995.1.DEN.26D4.GRT.157.59 24 38G4 V 1
#> 212 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 213 1991.1.GFR.06S1.CHP.2406.29 24 39G3 V 1
#> 214 1991.1.GFR.06S1.CHP.26071.48 26 38G8 V 1
#> 215 2003.4.DEN.26D4.TVL.49.24 25 39G5 V 1
#> 216 2011.4.DEN.26D4.TVL.39.42 25 40G4 V 1
#> 217 2002.4.GFR.06S1.TVS.43.33 24 39G4 V 3
#> 218 1994.1.DEN.26D4.GRT.68.34 26 39G8 V 1
#> 219 2010.1.DEN.26D4.TVL.100.1 25 39G6 V 1
#> 220 2010.1.DEN.26D4.TVL.102.2 25 39G6 V 1
#> 221 2010.1.DEN.26D4.TVL.124.5 25 39G5 V 1
#> 222 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 223 2010.1.DEN.26D4.TVL.45.39 25 39G5 V 1
#> 224 2004.1.POL.67BC.TVL.31.31 25 38G5 V 3
#> 225 2004.4.RUS.RUNT.TVL.NA.68 26 38G9 V 1
#> 226 2000.1.LAT.AA36.LBT.1.8 26 41G9 V 1
#> 227 2000.1.SWE.77AR.GOV.251.45 27 43G7 V 1
#> 228 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 229 2007.4.POL.67BC.TVL.26132.1 26 38G8 V 3
#> 230 2009.1.DEN.26D4.TVL.70.46 25 40G5 V 1
#> 231 2005.1.DEN.26D4.TVL.108.10 25 39G6 V 1
#> 232 2008.4.DEN.26D4.TVL.163.12 25 39G6 V 1
#> 233 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 234 1998.1.POL.67BC.P20.01Jan.46 25 39G7 V 3
#> 235 1999.1.DEN.26D4.GRT.69.32 26 41G8 V 1
#> 236 1999.1.DEN.26D4.GRT.96.44 26 39G8 V 1
#> 237 1999.4.DEN.26D4.TVL.100030.18 25 39G6 V 1
#> 238 2011.1.SWE.77MA.TVL.52.9 25 40G5 V 1
#> 239 2011.1.RUS.RUJB.TVL.56.40 26 39G9 V 1
#> 240 2011.4.DEN.26D4.TVL.173.15 25 39G6 V 1
#> 241 1995.1.GFR.06S1.H20.32.31 24 38G3 V 1
#> 242 1995.1.GFR.06S1.H20.66.83 25 41G7 V 1
#> 243 2003.1.DEN.26D4.TVL.91.47 25 40G7 V 1
#> 244 2003.4.GFR.06S1.TVS.24100.50 24 39G3 V 1
#> 245 2002.1.DEN.26D4.TVL.8.4 24 39G3 V 1
#> 246 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 247 1993.1.SWE.77AR.FOT.79.31 25 39G6 V 1
#> 248 1994.1.SWE.77AR.GOV.82.31 24 39G4 V 1
#> 249 1994.4.GFR.06S1.H20.33.53 24 38G3 V 1
#> 250 1991.1.GFR.06S1.CHP.2503.32 25 39G5 V 1
#> 251 2000.1.DEN.26D4.GRT.30.15 25 40G7 V 1
#> 252 2000.1.GFR.06S1.H20.82.98 25 39G7 V 1
#> 253 2000.4.DEN.26D4.TVL.80.41 26 39G8 V 1
#> 254 2007.4.GFR.06SL.TVS.24047.43 24 38G4 V 1
#> 255 1996.1.DEN.26D4.GRT.132.57 24 38G3 V 1
#> 256 1996.1.RUS.RUEK.DT.NA.17 26 40G8 V 1
#> 257 1996.1.SWE.77AR.FOT.76.25 26 40G8 V 1
#> 258 1997.1.SWE.77AR.FOT.204.25 28 43H0 V 1
#> 259 1997.4.LAT.AA36.LBT.2.19 26 41G9 V 1
#> 260 2008.1.LAT.67BC.TVL.1.30 26 40G9 V 1
#> 261 2008.4.DEN.26D4.TVL.132.7 24 38G4 V 1
#> 262 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 263 1992.1.SWE.77AR.GOV.58.9 24 39G4 V 1
#> 264 2005.1.SWE.77AR.TVL.238.44 25 40G4 V 1
#> 265 2005.1.RUS.RUNT.TVL.NA.23 26 39G9 V 1
#> 266 2005.4.POL.67BC.TVL.NA.34 26 39G9 V 3
#> 267 1998.1.DEN.26D4.GRT.138.65 26 39G8 V 1
#> 268 1998.1.GFR.06S1.H20.78.85 25 40G5 V 1
#> 269 1998.1.SWE.77AR.FOT.207.15 25 40G7 V 1
#> 270 1999.1.DEN.26D4.GRT.58.27 25 41G7 V 1
#> 271 1999.1.DEN.26D4.GRT.54.25 25 41G7 V 1
#> 272 1999.1.GFR.06S1.H20.50.71 24 39G3 V 1
#> 273 1999.1.DEN.26D4.TVL.151.88 25 38G5 V 1
#> 274 1999.1.SWE.77AR.FOT.214.21 24 39G3 V 1
#> 275 2011.1.POL.67BC.TVL.26182.32 26 39G8 V 1
#> 276 2003.1.RUS.RUNT.TVL.NA.34 26 39H0 V 1
#> 277 2003.4.DEN.26D4.TVL.80.31 25 38G5 V 1
#> 278 2002.1.DEN.26D4.TVL.133.55 25 39G6 V 1
#> 279 2002.1.RUS.RUS6.TVL.NA.7 26 39H0 V 1
#> 280 2002.1.POL.67BC.TVL.15.15 25 39G7 V 3
#> 281 1995.1.DEN.26D4.GRT.67.28 26 40G9 V 1
#> 282 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 283 1995.4.SWE.77AR.FOT.252.7 26 41G8 V 1
#> 284 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 285 1993.1.DEN.26D4.GRT.13.7 24 39G3 V 1
#> 286 1993.1.POL.AA36.P20.02Feb.37 25 39G5 V 1
#> 287 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 288 1991.1.POL.AA36.P20.03Mar.19 26 38G8 V 1
#> 289 2004.1.GFR.06S1.TVS.24012.53 24 38G3 V 1
#> 290 2007.4.SWE.77AR.TVL.696.21 25 40G4 V 1
#> 291 1996.4.GFR.06S1.H20.25.68 24 38G3 V 1
#> 292 2009.1.POL.67BC.TVL.25056.16 25 38G5 V 1
#> 293 2005.1.DEN.26D4.TVL.84.60 25 39G6 V 1
#> 294 2005.1.DEN.26D4.TVL.8.57 25 38G5 V 1
#> 295 1997.1.POL.67BC.P20.01Jan.15 26 38G9 V 3
#> 296 1997.1.DEN.26D4.GRT.64.30 24 38G3 V 1
#> 297 1997.1.POL.67BC.P20.03Mar.44 25 39G7 V 1
#> 298 1997.4.LAT.AA36.LBT.2.9 26 41G9 V 1
#> 299 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 300 1998.1.SWE.77AR.FOT.206.14 25 40G7 V 1
#> 301 1998.4.GFR.06S1.H20.35.75 24 38G3 V 1
#> 302 1999.1.DEN.26D4.GRT.96.44 26 39G8 V 1
#> 303 2003.4.DEN.26D4.TVL.81.32 25 38G5 V 1
#> 304 2003.4.RUS.RUJB.TVL.NA.66 26 39G9 V 1
#> 305 2002.4.SWE.77AR.TVL.575.13 25 40G7 V 1
#> 306 1994.1.SWE.77AR.FOT.60.9 25 40G7 V 1
#> 307 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 308 1995.4.SWE.77AR.FOT.267.22 25 40G4 V 1
#> 309 2010.1.RUS.RUNT.TVL.60.17 26 39G8 V 1
#> 310 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 311 1993.1.SWE.77AR.GOV.88.40 24 39G3 V 1
#> 312 1993.1.SWE.77AR.FOT.82.34 25 40G6 V 1
#> 313 1993.1.SWE.77AR.FOT.79.31 25 39G6 V 1
#> 314 2004.1.POL.67BC.TVL.2.2 26 39G8 V 3
#> 315 2004.4.POL.67BC.TVL.NA.8 26 38G8 V 3
#> 316 1991.1.DEN.26D4.GRT.83.46 26 40G9 V 1
#> 317 1991.1.GFR.06S1.CHP.2602.43 26 41G8 V 1
#> 318 1991.1.GFR.06S1.CHP.2604.44 26 41G8 V 1
#> 319 2000.1.GFR.06S1.H20.69.84 25 40G6 V 1
#> 320 2000.1.DEN.26D4.GRT.30.15 25 40G7 V 1
#> 321 2000.1.SWE.77AR.GOV.237.34 25 40G5 V 1
#> 322 2008.1.DEN.26D4.TVL.83.49 25 40G6 V 1
#> 323 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 324 1996.1.GFR.06S1.H20.82.113 25 39G7 V 1
#> 325 1996.4.GFR.06S1.H20.47.45 24 39G4 V 1
#> 326 1997.1.DEN.26D4.GRT.22.9 25 40G7 V 1
#> 327 1997.1.SWE.77AR.FOT.198.20 25 41G7 V 1
#> 328 1997.4.SWE.77AR.FOT.756.26 26 41G8 V 1
#> 329 1992.1.SWE.77AR.FOT.74.25 27 43G7 V 1
#> 330 1998.1.DEN.26D4.GRT.40.19 25 40G7 V 1
#> 331 2001.4.DEN.26D4.TVL.76.35 26 39G8 V 1
#> 332 1999.4.LAT.AA36.LBT.2.8 26 41H0 V 1
#> 333 2011.4.DEN.26D4.TVL.39.42 25 40G4 V 1
#> 334 2002.1.DEN.26D4.TVL.8.4 24 39G3 V 1
#> 335 2002.4.SWE.77AR.TVL.574.12 25 41G7 V 1
#> 336 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 337 1994.1.SWE.77AR.FOT.76.25 28 43G8 V 1
#> 338 1994.4.SWE.77AR.FOT.265.10 25 40G4 V 1
#> 339 1995.1.LAT.RUEK.DT.000001.23 26 41H0 V 1
#> 340 1995.1.SWE.77AR.GOV.82.30 28 43G9 V 1
#> 341 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 342 1993.1.SWE.77AR.GOV.88.40 24 39G3 V 1
#> 343 1993.4.GFR.06S1.H20.25.64 24 38G3 V 1
#> 344 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 345 2008.4.POL.67BC.TVL.26182.14 26 39G8 V 3
#> 346 2000.1.DEN.26D4.GRT.68.33 26 39G8 V 1
#> 347 2000.1.SWE.77AR.GOV.235.32 25 40G6 V 1
#> 348 2000.4.SWE.77AR.GOV.579.13 24 39G3 V 1
#> 349 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 350 1991.1.GFR.06S1.CHP.25232.67 25 38G5 V 1
#> 351 2005.1.DEN.26D4.TVL.20.25 25 39G6 V 1
#> 352 2005.1.DEN.26D4.TVL.99.70 24 38G4 V 1
#> 353 2005.1.DEN.26D4.TVL.26.28 25 39G6 V 1
#> 354 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 355 2009.4.POL.67BC.TVL.NA.4 26 37G9 V 1
#> 356 1996.1.DEN.26D4.GRT.76.41 25 39G6 V 1
#> 357 1996.1.DEN.26D4.GRT.57.31 26 41G9 V 1
#> 358 1996.1.DEN.26D4.GRT.65.35 25 40G7 V 1
#> 359 1996.1.SWE.77AR.FOT.77.26 26 40G9 V 1
#> 360 1997.1.RUS.RUNT.HAK.NA.40 26 41H0 V 1
#> 361 1997.4.LAT.AA36.LBT.2.13 28 42H0 V 1
#> 362 1998.1.DEN.26D4.GRT.91.43 26 41G8 V 1
#> 363 1998.1.DEN.26D4.GRT.138.65 26 39G8 V 1
#> 364 1998.1.RUS.RUJB.HAK.NA.34 26 40G9 V 1
#> 365 1998.1.SWE.77AR.FOT.248.44 25 40G5 V 1
#> 366 1998.1.POL.67BC.P20.01Jan.39 25 39G7 V 3
#> 367 1998.1.SWE.77AR.FOT.206.14 25 40G7 V 1
#> 368 1998.1.RUS.RUJB.HAK.NA.16 26 38G9 V 1
#> 369 1998.4.SWE.77AR.FOT.731.29 28 44G9 V 1
#> 370 2001.1.DEN.26D4.TVL.8.4 24 39G3 V 1
#> 371 2001.1.DEN.26D4.TVL.56.27 25 39G6 V 1
#> 372 2001.4.DEN.26D4.TVL.72.33 25 38G7 V 1
#> 373 1999.4.SWE.77AR.FOT.671.33 25 40G5 V 1
#> 374 1999.4.SWE.77AR.FOT.663.27 26 41G8 V 1
#> 375 2003.4.DEN.26D4.TVL.13.6 25 39G6 V 1
#> 376 2010.4.DEN.26D4.TVL.38.43 25 40G7 V 1
#> 377 2002.4.DEN.26D4.TVL.77.34 26 39G9 V 1
#> 378 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 379 1994.1.SWE.77AR.GOV.91.40 25 40G6 V 1
#> 380 2004.1.SWE.77AR.TVL.252.23 27 42G6 V 1
#> 381 2007.4.GFR.06SL.TVS.24300.51 24 38G4 V 1
#> 382 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 383 1995.1.RUS.RUEK.DT.NA.14 26 38G9 V 1
#> 384 1995.4.SWE.77AR.FOT.252.7 26 41G8 V 1
#> 385 1993.1.DEN.26D4.GRT.75.33 26 41G8 V 1
#> 386 1993.1.DEN.26D4.GRT.79.37 26 41G8 V 1
#> 387 1993.1.POL.AA36.P20.02Feb.48 25 39G7 V 1
#> 388 1993.1.POL.AA36.P20.02Feb.50 25 39G7 V 1
#> 389 1993.1.SWE.77AR.FOT.79.31 25 39G6 V 1
#> 390 2012.4.DEN.26D4.TVL.40.11 25 39G7 V 1
#> 391 2000.1.DEN.26D4.TVL.158.79 25 40G7 V 1
#> 392 2000.1.DEN.26D4.GRT.30.15 25 40G7 V 1
#> 393 2000.1.RUS.RUNT.HAK.NA.15 26 39H0 V 1
#> 394 2005.4.POL.67BC.TVL.NA.30 26 37G9 V 3
#> 395 2009.1.DEN.26D4.TVL.266.37 25 39G6 V 1
#> 396 2009.1.DEN.26D4.TVL.274.40 25 39G5 V 1
#> 397 2009.1.SWE.77AR.TVL.260.46 24 39G4 V 1
#> 398 2009.4.DEN.26D4.TVL.9.51 24 39G4 V 1
#> 399 2009.4.POL.67BC.TVL.NA.30 26 38G8 V 1
#> 400 1996.4.SWE.77AR.FOT.223.18 25 40G7 V 1
#> 401 1991.1.DEN.26D4.GRT.120.60 25 39G6 V 1
#> 402 1991.1.LAT.90MX.LBT.000001.11 26 41H0 V 1
#> 403 1991.1.LAT.90MX.LBT.000001.19 26 40H0 V 1
#> 404 1991.4.GFR.06S1.H20.42.43 24 38G3 V 1
#> 405 1997.1.DEN.26D4.GRT.56.26 26 39G8 V 1
#> 406 1997.1.POL.67BC.P20.01Jan.22 26 38G8 V 3
#> 407 1997.1.RUS.RUNT.HAK.NA.18 26 38G9 V 1
#> 408 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 409 1992.4.GFR.06S1.H20.25.23 24 38G3 V 1
#> 410 2011.1.DEN.26D4.TVL.113.4 25 39G7 V 1
#> 411 1998.1.DEN.26D4.GRT.80.39 25 38G5 V 1
#> 412 1998.1.GFR.06S1.H20.66.69 25 41G7 V 1
#> 413 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 414 1998.1.SWE.77AR.FOT.205.13 25 41G7 V 1
#> 415 1999.1.POL.67BC.P20.03Mar.70 26 38G9 V 1
#> 416 1999.1.POL.67BC.P20.02Feb.9 26 38G9 V 1
#> 417 1999.1.SWE.77AR.FOT.198.7 25 40G7 V 1
#> 418 2010.1.RUS.RUNT.TVL.60.16 26 39G8 V 1
#> 419 2010.4.DEN.26D4.TVL.78.48 25 39G7 V 1
#> 420 2003.1.DEN.26D4.TVL.44.23 25 39G7 V 1
#> 421 2003.1.GFR.06S1.TVS.2024.27 24 39G3 V 1
#> 422 2003.1.SWE.77AR.TVL.219.2 25 40G4 V 1
#> 423 2002.1.SWE.77AR.TVL.185.10 25 40G5 V 1
#> 424 2002.1.SWE.77AR.TVL.180.5 25 40G7 V 1
#> 425 2002.4.SWE.77AR.TVL.588.22 25 40G4 V 1
#> 426 2007.1.RUS.RUNT.TVL.52.3 26 38G9 V 1
#> 427 2007.4.DEN.26D4.TVL.3.44 25 39G5 V 1
#> 428 2006.4.DEN.26D4.TVL.65.29 25 39G6 V 1
#> 429 2008.1.DEN.26D4.TVL.81.48 25 40G6 V 1
#> 430 2008.4.POL.67BC.TVL.26183.1 26 38G8 V 3
#> 431 2008.4.RUS.RUJB.TVL.51.27 26 39G9 V 1
#> 432 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 433 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 434 1995.1.RUS.RUEK.DT.NA.31 26 39G9 V 1
#> 435 1995.1.SWE.77AR.GOV.64.12 25 39G6 V 1
#> 436 2014.1.GFR.06SL.TVS.25182.89 25 38G5 V 1
#> 437 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 438 2005.1.DEN.26D4.TVL.18.23 25 38G5 V 1
#> 439 2005.1.POL.67BC.TVL.4.4 26 38G8 V 3
#> 440 2005.4.DEN.26D4.TVL.4.20 25 39G7 V 1
#> 441 2005.4.POL.67BC.TVL.NA.30 26 37G9 V 3
#> 442 2009.1.POL.67BC.TVL.25056.16 25 38G5 V 1
#> 443 2009.1.RUS.RUNT.TVL.57.17 26 39G9 V 3
#> 444 2009.1.SWE.77AR.TVL.244.31 25 40G6 V 1
#> 445 2000.4.DEN.26D4.TVL.80.41 26 39G8 V 1
#> 446 2000.4.SWE.77AR.GOV.611.42 27 42G7 V 1
#> 447 1996.1.DEN.26D4.GRT.109.46 25 39G5 V 1
#> 448 1996.1.DEN.26D4.GRT.111.47 25 39G5 V 1
#> 449 1996.1.DEN.26D4.GRT.69.38 26 39G8 V 1
#> 450 1996.1.RUS.RUEK.DT.NA.23 26 39G9 V 1
#> 451 1996.1.SWE.77AR.FOT.73.22 25 40G6 V 1
#> 452 1996.1.SWE.77AR.FOT.99.48 25 41G7 V 1
#> 453 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 454 1991.1.DEN.26D4.GRT.69.37 26 41G9 V 1
#> 455 1991.1.DEN.26D4.GRT.75.40 28 42G9 V 1
#> 456 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 457 1991.1.DEN.26D4.GRT.82.45 26 40G9 V 1
#> 458 1991.1.GFR.06S1.CHP.26061.46 26 40G8 V 1
#> 459 1991.1.GFR.06S1.CHP.26071.48 26 38G8 V 1
#> 460 1991.1.GFR.06S1.CHP.2518.56 25 39G6 V 1
#> 461 1997.1.DEN.26D4.GRT.112.49 25 40G5 V 1
#> 462 1997.1.DEN.26D4.GRT.58.27 25 40G7 V 1
#> 463 1997.1.POL.67BC.P20.01Jan.43 25 39G7 V 3
#> 464 1997.1.DEN.26D4.GRT.24.10 25 40G7 V 1
#> 465 1997.1.POL.67BC.P20.03Mar.45 25 39G7 V 1
#> 466 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> 467 2011.1.DEN.26D4.TVL.87.54 25 39G6 V 1
#> 468 1992.1.GFR.06S1.CHP.26011.28 26 41G8 V 1
#> 469 1992.1.GFR.06S1.CHP.26022.40 26 41G8 V 1
#> 470 1998.1.DEN.26D4.GRT.105.49 28 43G8 V 1
#> 471 1998.1.DEN.26D4.GRT.28.13 25 39G7 V 1
#> 472 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 473 1998.1.RUS.RUJB.HAK.NA.1 26 40H0 V 1
#> 474 1998.1.POL.67BC.P20.01Jan.17 26 38G8 V 3
#> 475 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 476 1998.1.RUS.RUJB.HAK.NA.37 26 40H0 V 1
#> 477 1999.1.POL.67BC.P20.03Mar.59 26 39G8 V 1
#> 478 2010.1.GFR.06SL.TVS.24067.55 24 38G3 V 1
#> 479 2010.1.GFR.06SL.TVS.24210.23 24 39G3 V 1
#> 480 2003.1.DEN.26D4.TVL.71.36 25 39G5 V 1
#> 481 2003.1.GFR.06S1.TVS.2024.27 24 39G3 V 1
#> 482 2003.1.GFR.06S1.TVS.774.15 24 38G2 V 1
#> 483 2003.1.RUS.RUNT.TVL.NA.8 26 38G9 V 1
#> 484 2003.4.DEN.26D4.TVL.13.6 25 39G6 V 1
#> 485 2003.4.RUS.RUJB.TVL.NA.64 26 38G9 V 1
#> 486 2002.4.DEN.26D4.TVL.13.6 25 39G7 V 1
#> 487 2002.4.SWE.77AR.TVL.581.17 25 40G6 V 1
#> 488 2002.4.SWE.77AR.TVL.576.14 25 40G7 V 1
#> 489 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 490 2006.1.DEN.26D4.TVL.46.25 25 39G6 V 1
#> 491 2006.1.RUS.RUJB.TVL.NA.25 26 40G8 V 1
#> 492 2006.4.DEN.26D4.TVL.69.31 25 39G7 V 1
#> 493 1994.1.DEN.26D4.GRT.158.71 24 38G4 V 1
#> 494 1994.1.GFR.06S1.H20.25.2 24 38G3 V 1
#> 495 1994.1.SWE.77AR.GOV.89.38 24 39G3 V 1
#> 496 1994.1.POL.67BC.P20.Jan.33 26 38G8 V 3
#> 497 2004.1.DEN.26D4.TVL.82.41 25 39G6 V 1
#> 498 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 499 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 500 2012.1.DEN.26D4.TVL.62.47 25 39G5 V 1
#> 501 2012.1.DEN.26D4.TVL.172.14 25 39G7 V 1
#> 502 1995.1.DEN.26D4.GRT.44.19 28 43G9 V 1
#> 503 1995.1.SWE.77AR.GOV.66.14 26 40G8 V 1
#> 504 2005.4.DEN.26D4.TVL.22.10 26 40G8 V 1
#> 505 2009.4.DEN.26D4.TVL.199.17 25 39G6 V 1
#> 506 2009.4.SWE.77AR.TVL.742.30 25 40G4 V 1
#> 507 2009.4.POL.67BC.TVL.25052.17 25 38G6 V 1
#> 508 2000.1.GFR.06S1.H20.45.55 24 39G3 V 1
#> 509 2000.1.RUS.RUNT.HAK.NA.18 26 39G9 V 1
#> 510 2000.1.SWE.77AR.GOV.212.14 25 40G4 V 1
#> 511 2000.1.SWE.77AR.GOV.240.37 25 40G7 V 1
#> 512 2000.4.GFR.06S1.H20.50.65 24 39G3 V 1
#> 513 1993.1.DEN.26D4.GRT.11.6 24 39G3 V 1
#> 514 1993.1.DEN.26D4.GRT.95.43 28 43G8 V 1
#> 515 1993.1.POL.AA36.P20.02Feb.29 26 38G9 V 1
#> 516 1996.1.DEN.26D4.GRT.57.31 26 41G9 V 1
#> 517 1996.1.RUS.RUEK.DT.NA.13 26 39G8 V 1
#> 518 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 519 1997.1.POL.67BC.P20.01Jan.43 25 39G7 V 3
#> 520 1997.4.SWE.77AR.FOT.750.21 25 40G5 V 1
#> 521 1997.4.SWE.77AR.FOT.771.38 27 43G7 V 1
#> 522 1991.1.DEN.26D4.GRT.8.7 24 39G3 V 1
#> 523 1991.1.GFR.06S1.CHP.2407.30 24 39G3 V 1
#> 524 1991.1.GFR.06S1.CHP.25274.74 25 38G5 V 1
#> 525 1991.1.POL.AA36.P20.01Jan.26 26 38G9 V 3
#> 526 2011.4.DEN.26D4.TVL.175.16 25 39G6 V 1
#> 527 2001.4.DEN.26D4.TVL.62.30 25 39G7 V 1
#> 528 2001.4.DEN.26D4.TVL.73.34 26 39G8 V 1
#> 529 1992.1.DEN.26D4.GRT.82.57 25 39G6 V 1
#> 530 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 531 1992.1.DEN.26D4.GRT.60.43 26 41G8 V 1
#> 532 1998.1.DEN.26D4.GRT.69.34 25 39G5 V 1
#> 533 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 534 1998.1.POL.67BC.P20.03Mar.67 25 39G7 V 1
#> 535 1998.1.SWE.77AR.FOT.249.45 25 40G6 V 1
#> 536 1998.1.SWE.77AR.FOT.223.27 28 43H0 V 1
#> 537 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 538 1998.4.GFR.06S1.H20.30.73 24 38G3 V 1
#> 539 1999.1.POL.67BC.P20.03Mar.70 26 38G9 V 1
#> 540 1999.4.DEN.26D4.TVL.100030.18 25 39G6 V 1
#> 541 1999.4.SWE.77AR.FOT.663.27 26 41G8 V 1
#> 542 2010.1.GFR.06SL.TVS.24312.24 24 39G3 V 1
#> 543 2010.1.DEN.26D4.TVL.143.8 25 40G5 V 1
#> 544 2010.1.DEN.26D4.TVL.190.19 25 39G6 V 1
#> 545 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 546 2010.1.DEN.26D4.TVL.24.32 24 39G4 V 1
#> 547 2010.1.GFR.06SL.TVS.24237.31 24 39G4 V 1
#> 548 2010.4.DEN.26D4.TVL.78.48 25 39G7 V 1
#> 549 2010.4.DEN.26D4.TVL.194.22 25 38G5 V 1
#> 550 2010.4.RUS.RUJB.TVL.55.17 26 39G9 V 1
#> 551 2007.4.POL.67BC.TVL.25018.14 25 38G7 V 3
#> 552 2003.1.DEN.26D4.TVL.24.12 25 39G6 V 1
#> 553 2003.1.GFR.06S1.TVS.670.50 24 38G4 V 1
#> 554 2006.1.RUS.RUJB.TVL.NA.2 26 39G9 V 1
#> 555 2006.1.RUS.RUJB.TVL.NA.3 26 38G9 V 1
#> 556 2006.1.DEN.26D4.TVL.69.37 24 39G4 V 1
#> 557 2006.1.POL.67BC.TVL.25173.18 25 38G5 V 3
#> 558 2008.1.DEN.26D4.TVL.58.43 25 39G7 V 1
#> 559 2008.1.DEN.26D4.TVL.185.22 25 40G4 V 1
#> 560 2008.1.POL.67BC.TVL.25061.15 25 38G6 V 3
#> 561 2008.1.POL.67BC.TVL.25062.16 25 38G6 V 3
#> 562 2008.4.GFR.06SL.TVS.24142.28 24 39G4 V 1
#> 563 2008.4.DEN.26D4.TVL.132.7 24 38G4 V 1
#> 564 2008.4.RUS.RUJB.TVL.51.30 26 39G9 V 1
#> 565 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 566 2008.4.LAT.67BC.TVL.2.28 26 40H0 V 1
#> 567 2004.1.GFR.06S1.TVS.24202.15 24 38G2 V 1
#> 568 2004.4.DEN.26D4.TVL.54.25 25 40G6 V 1
#> 569 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 570 1994.1.POL.67BC.P20.Mar.12 26 38G8 V 1
#> 571 1994.1.POL.67BC.P20.Mar.9 26 38G8 V 1
#> 572 2012.4.POL.67BC.TVL.26020.34 26 38G8 V 1
#> 573 2005.1.DEN.26D4.TVL.84.60 25 39G6 V 1
#> 574 2005.1.DEN.26D4.TVL.39.34 26 39G8 V 1
#> 575 2005.1.DEN.26D4.TVL.10.1 25 38G5 V 1
#> 576 2005.1.RUS.RUNT.TVL.NA.46 26 41G8 V 1
#> 577 2005.4.POL.67BC.TVL.NA.26 25 39G7 V 3
#> 578 2005.4.POL.67BC.TVL.NA.35 26 39G8 V 3
#> 579 1995.1.DEN.26D4.GRT.38.16 28 42G8 V 1
#> 580 1995.1.LAT.RUEK.DT.000001.23 26 41H0 V 1
#> 581 1995.1.SWE.77AR.GOV.94.42 27 43G7 V 1
#> 582 1995.1.RUS.RUEK.DT.NA.1 26 40G9 V 1
#> 583 1995.4.SWE.77AR.FOT.267.22 25 40G4 V 1
#> 584 1995.4.SWE.77AR.FOT.252.7 26 41G8 V 1
#> 585 2009.1.DEN.26D4.TVL.262.35 25 39G6 V 1
#> 586 2009.1.DEN.26D4.TVL.198.19 25 39G6 V 1
#> 587 2009.1.DEN.26D4.TVL.266.37 25 39G6 V 1
#> 588 2009.1.RUS.RUNT.TVL.57.33 26 40G8 V 3
#> 589 2009.1.SWE.77AR.TVL.259.45 24 39G4 V 1
#> 590 2009.4.DEN.26D4.TVL.9.51 24 39G4 V 1
#> 591 2009.4.POL.67BC.TVL.26169.6 26 38G8 V 1
#> 592 2000.1.GFR.06S1.H20.64.81 25 40G6 V 1
#> 593 2000.1.RUS.RUNT.HAK.NA.5 26 38G9 V 1
#> 594 2000.1.RUS.RUNT.HAK.NA.29 26 40H0 V 1
#> 595 1993.1.DEN.26D4.GRT.162.72 25 38G5 V 1
#> 596 1993.1.DEN.26D4.GRT.13.7 24 39G3 V 1
#> 597 1993.1.LAT.LAIZ.LBT.000001.21 28 44H1 V 1
#> 598 1993.1.SWE.77AR.FOT.57.9 25 40G7 V 1
#> 599 1996.1.DEN.26D4.GRT.111.47 25 39G5 V 1
#> 600 1996.1.DEN.26D4.GRT.69.38 26 39G8 V 1
#> 601 1997.1.POL.67BC.P20.01Jan.30 26 38G8 V 3
#> 602 1997.1.RUS.RUNT.HAK.NA.40 26 41H0 V 1
#> 603 1997.1.RUS.RUNT.HAK.NA.26 26 39H0 V 1
#> 604 1997.4.SWE.77AR.FOT.744.15 25 40G7 V 1
#> 605 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> 606 2011.1.DEN.26D4.TVL.66.49 25 39G6 V 1
#> 607 2011.1.POL.67BC.TVL.26182.32 26 39G8 V 1
#> 608 2011.4.DEN.26D4.TVL.173.15 25 39G6 V 1
#> 609 1991.1.DEN.26D4.GRT.122.62 25 39G6 V 1
#> 610 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 611 1991.1.DEN.26D4.GRT.80.43 26 41G9 V 1
#> 612 1991.1.GFR.06S1.CHP.2509.35 25 40G6 V 1
#> 613 1991.1.POL.AA36.P20.03Mar.3 26 38G9 V 1
#> 614 1991.1.POL.AA36.P20.01Jan.22 26 37G9 V 3
#> 615 1991.1.LAT.90MX.LBT.000003.12 25 38G5 V 1
#> 616 2001.4.SWE.77AR.TVL.611.19 25 40G7 V 1
#> 617 1998.1.DEN.26D4.GRT.28.13 25 39G7 V 1
#> 618 1998.1.DEN.26D4.GRT.131.62 26 40G9 V 1
#> 619 1998.1.RUS.RUJB.HAK.NA.36 26 39G9 V 1
#> 620 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 621 1992.1.SWE.77AR.GOV.87.38 25 40G5 V 1
#> 622 1999.1.DEN.26D4.GRT.21.11 25 39G5 V 1
#> 623 2007.1.POL.67BC.TVL.25394.29 25 38G5 V 3
#> 624 2007.4.DEN.26D4.TVL.167.14 25 40G6 V 1
#> 625 2007.4.POL.67BC.TVL.26044.7 26 39G8 V 3
#> 626 2007.4.POL.67BC.TVL.26182.8 26 39G8 V 3
#> 627 2006.1.DEN.26D4.TVL.55.30 25 39G5 V 1
#> 628 2006.1.RUS.RUJB.TVL.NA.36 26 39H0 V 1
#> 629 2006.1.DEN.26D4.TVL.81.44 25 40G6 V 1
#> 630 2008.4.POL.67BC.TVL.25010.3 25 37G6 V 3
#> 631 2003.1.DEN.26D4.TVL.33.17 25 39G6 V 1
#> 632 2003.1.DEN.26D4.TVL.75.38 25 40G5 V 1
#> 633 2003.4.RUS.RUJB.TVL.NA.54 26 40G9 V 1
#> 634 2003.4.POL.67BC.TVL.NA.24 25 38G5 V 3
#> 635 2002.1.RUS.RUS6.TVL.NA.22 26 39G9 V 1
#> 636 2002.1.RUS.RUS6.TVL.NA.25 26 40G9 V 1
#> 637 2004.1.DEN.26D4.TVL.82.41 25 39G6 V 1
#> 638 2004.1.DEN.26D4.TVL.24.9 25 39G7 V 1
#> 639 2004.1.DEN.26D4.TVL.10.1 25 39G7 V 1
#> 640 2004.1.POL.67BC.TVL.2.2 26 39G8 V 3
#> 641 2004.4.POL.67BC.TVL.NA.1 26 37G9 V 3
#> 642 2004.4.POL.67BC.TVL.NA.8 26 38G8 V 3
#> 643 2014.1.GFR.06SL.TVS.24202.38 24 38G4 V 1
#> 644 2014.4.POL.67BC.TVL.26133.31 26 38G8 V 1
#> 645 2005.1.POL.67BC.TVL.4.4 26 38G8 V 3
#> 646 2005.1.RUS.RUNT.TVL.NA.21 26 39H0 V 1
#> 647 2005.4.POL.67BC.TVL.NA.41 25 39G7 V 3
#> 648 2005.4.RUS.RUJB.TVL.36.43 26 38G9 V 1
#> 649 2009.1.DEN.26D4.TVL.198.19 25 39G6 V 1
#> 650 2009.1.DEN.26D4.TVL.175.13 25 38G5 V 1
#> 651 2009.4.GFR.06SL.TVS.24251.48 24 39G4 V 1
#> 652 1995.1.DEN.26D4.GRT.57.23 26 41G9 V 1
#> 653 1995.1.LAT.RUEK.DT.000001.19 28 42H0 V 1
#> 654 1995.1.SWE.77AR.GOV.84.32 28 43H0 V 1
#> 655 2000.1.SWE.77AR.GOV.235.32 25 40G6 V 1
#> 656 1993.1.GFR.06S1.H20.48.22 24 39G4 V 1
#> 657 1993.1.SWE.77AR.FOT.59.11 25 41G6 V 1
#> 658 1993.1.SWE.77AR.FOT.80.32 25 39G5 V 1
#> 659 1993.1.SWE.77AR.FOT.77.29 26 40G8 V 1
#> 660 1996.1.DEN.26D4.GRT.43.23 28 42H0 V 1
#> 661 1996.1.GFR.06S1.H20.34.11 24 38G3 V 1
#> 662 1996.1.RUS.RUEK.DT.NA.17 26 40G8 V 1
#> 663 1996.1.SWE.77AR.FOT.71.20 25 40G6 V 1
#> 664 1996.1.LAT.RUEK.DT.000001.62 28 42H0 V 1
#> 665 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 666 1997.1.DEN.26D4.GRT.36.16 26 41G8 V 1
#> 667 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> 668 2011.1.DEN.26D4.TVL.66.49 25 39G6 V 1
#> 669 2011.1.POL.67BC.TVL.25039.16 25 37G5 V 1
#> 670 2001.1.GFR.06S1.TVS.1998.15 24 39G2 V 3
#> 671 2001.4.SWE.77AR.TVL.603.13 27 42G6 V 1
#> 672 2010.1.DEN.26D4.TVL.102.2 25 39G6 V 1
#> 673 2010.1.RUS.RUNT.TVL.60.10 26 40G8 V 1
#> 674 2010.1.RUS.RUNT.TVL.60.17 26 39G8 V 1
#> 675 2010.1.POL.67BC.TVL.26087.33 26 38G8 V 1
#> 676 2010.1.SWE.77AR.TVL.242.42 25 40G4 V 1
#> 677 2010.4.DEN.26D4.TVL.199.25 25 39G6 V 1
#> 678 2010.4.DEN.26D4.TVL.142.11 25 38G5 V 1
#> 679 2010.4.DEN.26D4.TVL.166.16 25 38G5 V 1
#> 680 1991.1.DEN.26D4.GRT.46.30 26 41G8 V 1
#> 681 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 682 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 683 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 684 1991.1.LAT.90MX.LBT.000001.17 26 39G9 V 1
#> 685 1991.1.GFR.06S1.CHP.25232.67 25 38G5 V 1
#> 686 1991.1.GFR.06S1.H20.21.25 24 38G3 V 1
#> 687 1991.1.POL.AA36.P20.03Mar.2 26 38G9 V 1
#> 688 1991.1.POL.AA36.P20.03Mar.27 26 38G9 V 1
#> 689 1998.1.DEN.26D4.GRT.80.39 25 38G5 V 1
#> 690 1998.1.DEN.26D4.GRT.28.13 25 39G7 V 1
#> 691 1998.1.GFR.06S1.H20.44.45 24 39G3 V 1
#> 692 1998.1.DEN.26D4.GRT.131.62 26 40G9 V 1
#> 693 1998.1.SWE.77AR.FOT.198.7 24 39G3 V 1
#> 694 1998.1.POL.67BC.P20.03Mar.12 26 38G9 V 1
#> 695 1998.1.POL.67BC.P20.03Mar.63 25 39G7 V 1
#> 696 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 697 1998.1.RUS.RUJB.HAK.NA.36 26 39G9 V 1
#> 698 2007.1.RUS.RUNT.TVL.52.1 26 39G9 V 1
#> 699 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 700 2006.4.POL.67BC.TVL.NA.29 25 39G7 V 3
#> 701 2006.4.DEN.26D4.TVL.47.19 25 40G6 V 1
#> 702 2006.4.DEN.26D4.TVL.65.29 25 39G6 V 1
#> 703 2006.4.POL.67BC.TVL.NA.27 25 39G7 V 3
#> 704 1992.1.DEN.26D4.GRT.82.57 25 39G6 V 1
#> 705 1992.1.GFR.06S1.CHP.2412.6 24 38G3 V 1
#> 706 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 707 1992.1.DEN.26D4.GRT.78.54 26 39G8 V 1
#> 708 1992.1.DEN.26D4.GRT.85.59 25 39G5 V 1
#> 709 1992.1.DEN.26D4.GRT.83.58 25 39G5 V 1
#> 710 1992.1.SWE.77AR.GOV.81.32 28 43G8 V 1
#> 711 1992.1.SWE.77AR.FOT.71.22 27 44G8 V 1
#> 712 1992.1.SWE.77AR.GOV.58.9 24 39G4 V 1
#> 713 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 714 1999.1.DEN.26D4.GRT.106.49 25 39G6 V 1
#> 715 1999.1.DEN.26D4.GRT.104.48 25 39G6 V 1
#> 716 1999.1.GFR.06S1.H20.44.69 24 39G3 V 1
#> 717 1999.1.GFR.06S1.H20.82.139 25 39G7 V 1
#> 718 1999.1.SWE.77AR.FOT.198.7 25 40G7 V 1
#> 719 1999.4.SWE.77AR.GOV.653.18 25 40G5 V 1
#> 720 1999.4.SWE.77AR.FOT.659.24 25 41G7 V 1
#> 721 2003.4.RUS.RUJB.TVL.NA.57 26 39H0 V 1
#> 722 2003.4.SWE.77AR.TVL.750.40 25 40G4 V 1
#> 723 2002.4.DEN.26D4.TVL.85.39 26 39H0 V 1
#> 724 2004.1.DEN.26D4.TVL.70.34 25 40G7 V 1
#> 725 1994.1.DEN.26D4.GRT.52.26 26 41G9 V 1
#> 726 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 727 1994.1.SWE.77AR.FOT.65.14 26 41G8 V 1
#> 728 2005.1.DEN.26D4.TVL.49.40 25 39G7 V 1
#> 729 2005.1.RUS.RUNT.TVL.NA.36 26 41G9 V 1
#> 730 2005.1.POL.67BC.TVL.34.34 26 37G9 V 3
#> 731 2005.1.POL.67BC.TVL.33.33 26 39G8 V 3
#> 732 2005.4.POL.67BC.TVL.NA.31 26 37G9 V 3
#> 733 2009.1.DEN.26D4.TVL.258.33 25 39G7 V 1
#> 734 2009.1.DEN.26D4.TVL.70.46 25 40G5 V 1
#> 735 2009.1.DEN.26D4.TVL.120.4 25 39G5 V 1
#> 736 2009.1.GFR.06SL.TVS.24211.47 24 39G3 V 1
#> 737 2009.1.DEN.26D4.TVL.266.37 25 39G6 V 1
#> 738 2009.1.POL.67BC.TVL.26107.29 26 40G8 V 1
#> 739 2009.4.DEN.26D4.TVL.9.51 24 39G4 V 1
#> 740 1995.1.RUS.RUEK.DT.NA.29 26 39H0 V 1
#> 741 1995.1.RUS.RUEK.DT.NA.1 26 40G9 V 1
#> 742 1995.4.SWE.77AR.FOT.258.13 28 44G9 V 1
#> 743 2000.1.DEN.26D4.GRT.24.12 25 40G7 V 1
#> 744 2000.1.DEN.26D4.GRT.160.81 25 40G7 V 1
#> 745 2000.1.SWE.77AR.FOT.270.47 27 42G7 V 1
#> 746 2000.1.SWE.77AR.GOV.240.37 25 40G7 V 1
#> 747 1996.1.DEN.26D4.GRT.51.29 26 41G9 V 1
#> 748 1996.1.SWE.77AR.FOT.96.45 27 43G7 V 1
#> 749 1996.1.POL.67BC.P20.01Jan.19 26 38G8 V 3
#> 750 1996.1.POL.67BC.P20.01Jan.26 26 38G8 V 3
#> 751 1996.1.SWE.77AR.FOT.90.39 28 43G8 V 1
#> 752 1996.1.SWE.77AR.FOT.58.7 24 39G3 V 1
#> 753 1996.4.SWE.77AR.FOT.228.23 26 41G8 V 1
#> 754 1993.1.DEN.26D4.GRT.117.56 26 41G9 V 1
#> 755 1993.1.LAT.LAIZ.LBT.000001.16 26 39G9 V 1
#> 756 1993.1.LAT.LAIZ.LBT.000001.18 28 42H0 V 1
#> 757 1993.1.POL.AA36.P20.01Jan.12 26 38G8 V 1
#> 758 1993.1.SWE.77AR.FOT.59.11 25 41G6 V 1
#> 759 2011.1.DEN.26D4.TVL.66.49 25 39G6 V 1
#> 760 2011.4.DEN.26D4.TVL.124.5 25 39G7 V 1
#> 761 2011.4.DEN.26D4.TVL.173.15 25 39G6 V 1
#> 762 2011.4.DEN.26D4.TVL.232.26 25 38G5 V 1
#> 763 1997.1.POL.67BC.P20.01Jan.36 26 38G8 V 3
#> 764 1997.1.POL.67BC.P20.03Mar.15 26 38G9 V 1
#> 765 1997.1.POL.67BC.P20.03Mar.59 25 38G5 V 1
#> 766 1997.1.RUS.RUNT.HAK.NA.37 26 40H0 V 1
#> 767 1997.1.SWE.77AR.FOT.200.22 26 41G8 V 1
#> 768 1997.4.SWE.77AR.FOT.747.18 25 40G5 V 1
#> 769 1997.4.SWE.77AR.FOT.745.16 25 41G7 V 1
#> 770 2010.1.DEN.26D4.TVL.169.11 25 40G5 V 1
#> 771 2010.1.DEN.26D4.TVL.243.34 25 40G6 V 1
#> 772 2010.1.GFR.06SL.TVS.24210.23 24 39G3 V 1
#> 773 2010.1.RUS.RUNT.TVL.60.17 26 39G8 V 1
#> 774 2010.1.RUS.RUNT.TVL.60.29 26 39G9 V 1
#> 775 2010.1.POL.67BC.TVL.26211.1 26 38G9 V 1
#> 776 2010.4.DEN.26D4.TVL.59.46 25 39G7 V 1
#> 777 2010.4.DEN.26D4.TVL.34.40 26 39G8 V 1
#> 778 2010.4.DEN.26D4.TVL.124.9 25 38G5 V 1
#> 779 2001.1.DEN.26D4.TVL.38.19 25 40G7 V 1
#> 780 2001.4.DEN.26D4.TVL.50.25 25 37G5 V 1
#> 781 2007.1.POL.67BC.TVL.26044.3 26 39G8 V 3
#> 782 2007.4.DEN.26D4.TVL.101.2 25 40G5 V 1
#> 783 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 784 2008.1.DEN.26D4.TVL.130.7 25 38G5 V 1
#> 785 2008.1.RUS.RUJB.TVL.49.2 26 39H0 V 1
#> 786 2008.4.POL.67BC.TVL.26182.14 26 39G8 V 3
#> 787 2008.4.SWE.77AR.TVL.719.25 25 40G4 V 1
#> 788 2006.1.GFR.06SL.TVS.24020.38 24 39G3 V 1
#> 789 2006.1.DEN.26D4.TVL.26.14 25 39G7 V 1
#> 790 1998.1.DEN.26D4.GRT.134.63 26 39G8 V 1
#> 791 1998.1.RUS.RUJB.HAK.NA.34 26 40G9 V 1
#> 792 1998.1.POL.67BC.P20.01Jan.46 25 39G7 V 3
#> 793 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 794 1998.1.RUS.RUJB.HAK.NA.37 26 40H0 V 1
#> 795 1991.1.DEN.26D4.GRT.29.19 25 40G7 V 1
#> 796 1991.1.DEN.26D4.GRT.37.25 26 41G8 V 1
#> 797 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 798 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 799 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 800 1991.1.POL.AA36.P20.01Jan.27 26 38G9 V 3
#> 801 1991.1.LAT.90MX.LBT.000003.14 26 38G9 V 1
#> 802 1999.1.GFR.06S1.H20.61.89 25 40G5 V 1
#> 803 1999.1.POL.67BC.P20.02Feb.8 26 38G8 V 1
#> 804 1999.1.LAT.AA36.LBT.000001.5 28 42H0 V 1
#> 805 1999.4.DEN.26D4.TVL.100004.2 25 40G5 V 1
#> 806 1999.4.SWE.77AR.FOT.658.23 25 41G7 V 1
#> 807 1999.4.LAT.AA36.LBT.2.14 28 42H0 V 1
#> 808 1999.4.LAT.AA36.LBT.2.8 26 41H0 V 1
#> 809 1992.1.DEN.26D4.GRT.54.38 26 41G8 V 1
#> 810 1992.1.DEN.26D4.GRT.61.44 28 42G8 V 1
#> 811 1992.1.GFR.06S1.CHP.28063.32 28 43H0 V 1
#> 812 1992.1.SWE.77AR.FOT.71.22 27 44G8 V 1
#> 813 2012.4.DEN.26D4.TVL.29.10 25 39G6 V 1
#> 814 2012.4.DEN.26D4.TVL.42.12 25 39G7 V 1
#> 815 2003.1.DEN.26D4.TVL.80.41 25 40G6 V 1
#> 816 2003.4.DEN.26D4.TVL.11.5 25 39G6 V 1
#> 817 2003.4.DEN.26D4.TVL.81.32 25 38G5 V 1
#> 818 2003.4.SWE.77AR.TVL.736.26 25 40G7 V 1
#> 819 2013.1.DEN.26D4.TVL.86.46 25 38G5 V 1
#> 820 2004.4.POL.67BC.TVL.NA.28 25 39G7 V 3
#> 821 2002.1.DEN.26D4.TVL.133.55 25 39G6 V 1
#> 822 2002.1.DEN.26D4.TVL.109.43 25 40G7 V 1
#> 823 2002.1.POL.67BC.TVL.16.16 25 39G7 V 3
#> 824 2002.1.RUS.RUS6.TVL.NA.12 26 38G9 V 1
#> 825 2002.4.DEN.26D4.TVL.42.20 25 39G6 V 1
#> 826 1994.1.DEN.26D4.GRT.64.33 26 39G8 V 1
#> 827 1994.1.SWE.77AR.GOV.82.31 24 39G4 V 1
#> 828 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 829 1994.1.SWE.77AR.FOT.65.14 26 41G8 V 1
#> 830 1994.1.SWE.77AR.FOT.60.9 25 40G7 V 1
#> 831 1994.1.POL.67BC.P20.Mar.5 26 38G8 V 1
#> 832 1994.4.SWE.77AR.FOT.281.26 28 43G8 V 1
#> 833 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 834 2005.1.DEN.26D4.TVL.22.26 25 39G6 V 1
#> 835 2009.1.LAT.67BC.TVL.1.30 26 40H0 V 1
#> 836 2009.1.GFR.06SL.TVS.24286.31 24 38G4 V 1
#> 837 2009.1.RUS.RUNT.TVL.57.35 26 40G8 V 3
#> 838 2009.1.RUS.RUNT.TVL.57.2 26 38G9 V 3
#> 839 2009.1.POL.67BC.TVL.26182.30 26 39G8 V 1
#> 840 2009.4.DEN.26D4.TVL.129.5 25 39G7 V 1
#> 841 2009.4.DEN.26D4.TVL.27.37 25 40G4 V 1
#> 842 2009.4.GFR.06SL.TVS.24169.60 24 38G3 V 1
#> 843 2009.4.POL.67BC.TVL.25013.18 25 38G6 V 1
#> 844 1995.1.DEN.26D4.GRT.23.9 25 41G7 V 1
#> 845 1995.1.DEN.26D4.GRT.8.2 25 39G6 V 1
#> 846 1995.1.GFR.06S1.H20.31.18 24 38G4 V 1
#> 847 1995.1.GFR.06S1.H20.80.91 25 39G6 V 1
#> 848 1995.1.RUS.RUEK.DT.NA.7 26 39G9 V 1
#> 849 2000.1.GFR.06S1.H20.82.98 25 39G7 V 1
#> 850 2000.1.SWE.77AR.GOV.242.39 25 41G7 V 1
#> 851 1996.1.DEN.26D4.GRT.32.18 26 41G8 V 1
#> 852 1996.1.DEN.26D4.GRT.65.35 25 40G7 V 1
#> 853 1996.1.POL.67BC.P20.03Mar.20 26 38G8 V 1
#> 854 1996.1.LAT.RUEK.DT.000001.64 28 42H0 V 1
#> 855 1996.1.SWE.77AR.FOT.57.6 24 39G3 V 1
#> 856 1996.4.SWE.77AR.FOT.229.24 26 41G8 V 1
#> 857 2011.1.DEN.26D4.TVL.87.54 25 39G6 V 1
#> 858 2011.1.POL.67BC.TVL.26182.32 26 39G8 V 1
#> 859 2011.1.RUS.RUJB.TVL.56.18 25 40G7 V 1
#> 860 2011.4.DEN.26D4.TVL.173.15 25 39G6 V 1
#> 861 2011.4.DEN.26D4.TVL.232.26 25 38G5 V 1
#> 862 1993.1.DEN.26D4.GRT.17.9 24 39G4 V 1
#> 863 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 864 1997.1.DEN.26D4.GRT.56.26 26 39G8 V 1
#> 865 1997.1.POL.67BC.P20.01Jan.30 26 38G8 V 3
#> 866 1997.1.POL.67BC.P20.01Jan.31 26 38G8 V 3
#> 867 1997.1.DEN.26D4.GRT.88.41 25 38G6 V 1
#> 868 1997.1.SWE.77AR.FOT.192.14 25 40G6 V 1
#> 869 1997.4.SWE.77AR.FOT.744.15 25 40G7 V 1
#> 870 2010.1.DEN.26D4.TVL.98.48 25 39G6 V 1
#> 871 2010.1.DEN.26D4.TVL.190.19 25 39G6 V 1
#> 872 2010.1.DEN.26D4.TVL.207.20 25 39G7 V 1
#> 873 2010.4.DEN.26D4.TVL.118.5 25 38G5 V 1
#> 874 2010.4.RUS.RUJB.TVL.55.17 26 39G9 V 1
#> 875 2008.1.DEN.26D4.TVL.35.38 25 39G7 V 1
#> 876 2008.1.DEN.26D4.TVL.133.9 25 38G5 V 1
#> 877 2008.4.DEN.26D4.TVL.155.10 25 39G7 V 1
#> 878 2008.4.DEN.26D4.TVL.157.11 25 39G7 V 1
#> 879 2007.1.POL.67BC.TVL.26020.1 26 38G8 V 3
#> 880 2007.4.GFR.06SL.TVS.24152.56 24 38G3 V 1
#> 881 2007.4.DEN.26D4.TVL.3.44 25 39G5 V 1
#> 882 2007.4.RUS.RUNT.TVL.55.35 26 38G9 V 1
#> 883 2001.1.DEN.26D4.TVL.131.54 25 40G4 V 1
#> 884 2006.1.DEN.26D4.TVL.19.10 25 39G7 V 1
#> 885 2006.4.POL.67BC.TVL.NA.29 25 39G7 V 3
#> 886 1998.1.GFR.06S1.H20.45.49 24 39G3 V 1
#> 887 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 888 1998.1.DEN.26D4.GRT.44.21 25 41G7 V 1
#> 889 1998.1.POL.67BC.P20.03Mar.56 25 38G6 V 1
#> 890 1998.1.SWE.77AR.FOT.228.29 28 44G9 V 1
#> 891 1999.1.DEN.26D4.GRT.111.52 25 39G6 V 1
#> 892 1999.1.DEN.26D4.GRT.52.24 25 40G7 V 1
#> 893 1999.1.GFR.06S1.H20.76.131 25 39G6 V 1
#> 894 1999.1.RUS.RUNT.HAK.NA.31 26 40H0 V 1
#> 895 1999.1.POL.67BC.P20.03Mar.70 26 38G9 V 1
#> 896 1999.1.POL.67BC.P20.02Feb.25 25 38G5 V 1
#> 897 1999.1.SWE.77AR.FOT.269.69 27 43G7 V 1
#> 898 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 899 1991.1.GFR.06S1.CHP.2604.44 26 41G8 V 1
#> 900 1991.1.LAT.90MX.LBT.000001.12 26 39H0 V 1
#> 901 1991.1.GFR.06S1.CHP.26071.48 26 38G8 V 1
#> 902 1991.1.GFR.06S1.CHP.2516.54 25 39G6 V 1
#> 903 1991.1.LAT.90MX.LBT.000001.19 26 40H0 V 1
#> 904 1991.1.POL.AA36.P20.03Mar.1 26 38G9 V 1
#> 905 1991.1.LAT.90MX.LBT.000003.21 26 39G9 V 1
#> 906 1991.1.POL.AA36.P20.01Jan.28 26 38G8 V 3
#> 907 1992.1.GFR.06S1.CHP.25081.21 25 40G5 V 1
#> 908 1992.1.GFR.06S1.CHP.2511.24 25 40G6 V 1
#> 909 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 910 2003.1.DEN.26D4.TVL.71.36 25 39G5 V 1
#> 911 2003.1.DEN.26D4.TVL.91.47 25 40G7 V 1
#> 912 2002.1.GFR.06S1.TVS.923.173 24 38G3 V 3
#> 913 2002.1.SWE.77AR.TVL.195.20 25 41G6 V 1
#> 914 2002.4.SWE.77AR.TVL.570.9 27 42G6 V 1
#> 915 1994.1.DEN.26D4.GRT.23.13 28 42G8 V 1
#> 916 1994.1.DEN.26D4.GRT.64.33 26 39G8 V 1
#> 917 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 918 1994.1.POL.67BC.P20.Mar.39 25 39G7 V 1
#> 919 1994.1.POL.67BC.P20.Mar.40 25 39G7 V 1
#> 920 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 921 2005.1.GFR.06SL.TVS.24041.46 24 38G4 V 1
#> 922 2005.1.POL.67BC.TVL.34.34 26 37G9 V 3
#> 923 2005.1.POL.67BC.TVL.4.4 26 38G8 V 3
#> 924 2005.1.RUS.RUNT.TVL.NA.23 26 39G9 V 1
#> 925 2005.4.RUS.RUJB.TVL.36.23 26 38G9 V 1
#> 926 2005.4.POL.67BC.TVL.NA.30 26 37G9 V 3
#> 927 2009.1.DEN.26D4.TVL.120.4 25 39G5 V 1
#> 928 2009.1.DEN.26D4.TVL.146.10 25 38G5 V 1
#> 929 2009.1.RUS.RUNT.TVL.57.4 26 39G9 V 3
#> 930 2009.4.DEN.26D4.TVL.78.48 25 40G6 V 1
#> 931 2009.4.DEN.26D4.TVL.9.51 24 39G4 V 1
#> 932 2009.4.DEN.26D4.TVL.176.14 25 39G7 V 1
#> 933 2009.4.SWE.77AR.TVL.739.27 24 39G4 V 1
#> 934 2009.4.POL.67BC.TVL.26186.2 26 37G9 V 1
#> 935 2009.4.POL.67BC.TVL.NA.27 26 37G9 V 1
#> 936 2000.1.DEN.26D4.GRT.78.38 25 40G7 V 1
#> 937 2000.1.POL.67BC.P20.NA.57 26 38G8 V 1
#> 938 2000.4.LAT.AA36.LBT.2.17 28 42H0 V 1
#> 939 1995.1.DEN.26D4.GRT.29.12 26 41G8 V 1
#> 940 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 941 1995.1.DEN.26D4.GRT.165.63 24 38G3 V 1
#> 942 1995.1.SWE.77AR.GOV.66.14 26 40G8 V 1
#> 943 1995.4.SWE.77AR.FOT.257.12 28 43G9 V 1
#> 944 2011.1.GFR.06SL.TVS.24212.24 24 38G3 V 1
#> 945 2011.4.POL.67BC.TVL.25051.16 25 38G5 V 1
#> 946 1996.1.DEN.26D4.GRT.46.26 26 41G9 V 1
#> 947 1996.1.GFR.06S1.H20.59.95 25 37G6 V 1
#> 948 1996.1.RUS.RUEK.DT.NA.17 26 40G8 V 1
#> 949 1996.1.POL.67BC.P20.01Jan.45 25 39G7 V 3
#> 950 1996.1.SWE.77AR.FOT.74.23 25 40G6 V 1
#> 951 1996.1.SWE.77AR.FOT.75.24 25 40G7 V 1
#> 952 1997.1.SWE.77AR.FOT.198.20 25 41G7 V 1
#> 953 1997.4.LAT.AA36.LBT.2.19 26 41G9 V 1
#> 954 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 955 1997.4.SWE.77AR.FOT.753.23 26 40G8 V 1
#> 956 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> 957 1993.1.GFR.06S1.H20.78.47 25 40G5 V 1
#> 958 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 959 1993.1.SWE.77AR.FOT.82.34 25 40G6 V 1
#> 960 1993.1.SWE.77AR.FOT.58.10 25 41G7 V 1
#> 961 1993.1.SWE.77AR.FOT.80.32 25 39G5 V 1
#> 962 2010.1.DEN.26D4.TVL.173.13 25 40G4 V 1
#> 963 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 964 2010.1.GFR.06SL.TVS.24104.22 24 39G3 V 1
#> 965 2010.1.RUS.RUNT.TVL.60.16 26 39G8 V 1
#> 966 2010.1.RUS.RUNT.TVL.60.23 26 38G9 V 1
#> 967 2010.1.SWE.77AR.TVL.240.40 25 40G4 V 1
#> 968 2010.4.DEN.26D4.TVL.118.5 25 38G5 V 1
#> 969 2010.4.DEN.26D4.TVL.59.46 25 39G7 V 1
#> 970 2010.4.DEN.26D4.TVL.142.11 25 38G5 V 1
#> 971 2010.4.RUS.RUJB.TVL.55.7 26 39H0 V 1
#> 972 2008.1.RUS.RUJB.TVL.49.2 26 39H0 V 1
#> 973 2008.1.RUS.RUJB.TVL.49.13 26 39G9 V 1
#> 974 2008.4.LTU.LTDA.TVS.26052.2 26 40H0 V 1
#> 975 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 976 2008.4.POL.67BC.TVL.26037.2 26 38G8 V 3
#> 977 2008.4.POL.67BC.TVL.26020.18 26 38G8 V 3
#> 978 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 979 2007.1.DEN.26D4.TVL.44.23 25 40G6 V 1
#> 980 2007.4.LTU.LTDA.TVS.Nov.2 26 40H0 V 1
#> 981 2007.4.DEN.26D4.TVL.3.44 25 39G5 V 1
#> 982 2007.4.POL.67BC.TVL.26132.1 26 38G8 V 3
#> 983 2006.4.POL.67BC.TVL.25017.10 25 38G6 V 3
#> 984 2001.1.SWE.77AR.TVL.231.25 28 43G8 V 1
#> 985 2001.1.RUS.RUNT.TVL.NA.51 26 41H0 V 1
#> 986 2001.1.POL.67BC.P20.NA.11 26 37G9 V 1
#> 987 2001.4.DEN.26D4.TVL.83.37 26 40G8 V 1
#> 988 2001.4.DEN.26D4.TVL.4.3 25 39G5 V 1
#> 989 2012.1.DEN.26D4.TVL.66.49 25 39G5 V 1
#> 990 1998.1.RUS.RUJB.HAK.NA.36 26 39G9 V 1
#> 991 2013.1.POL.67BC.TVL.25054.15 25 38G5 V 1
#> 992 2013.4.POL.67BC.TVL.25051.12 25 38G5 V 1
#> 993 2004.1.SWE.77AR.TVL.229.3 26 41G8 V 1
#> 994 2004.1.SWE.77AR.TVL.228.2 25 41G7 V 1
#> 995 2004.1.POL.67BC.TVL.42.42 26 39G8 V 3
#> 996 2004.4.DEN.26D4.TVL.30.12 26 40G8 V 1
#> 997 1999.1.GFR.06S1.H20.42.65 24 38G3 V 1
#> 998 1999.1.GFR.06S1.H20.44.69 24 39G3 V 1
#> 999 1999.1.LAT.AA36.LBT.000001.8 26 41H0 V 1
#> 1000 1999.4.SWE.77AR.GOV.652.17 25 40G5 V 1
#> 1001 1999.4.LAT.AA36.LBT.2.8 26 41H0 V 1
#> 1002 2003.1.SWE.77AR.TVL.239.16 25 40G7 V 1
#> 1003 2003.4.DEN.26D4.TVL.32.15 25 40G6 V 1
#> 1004 2003.4.DEN.26D4.TVL.49.24 25 39G5 V 1
#> 1005 2003.4.DEN.26D4.TVL.41.20 25 39G7 V 1
#> 1006 2002.1.DEN.26D4.TVL.48.27 25 40G6 V 1
#> 1007 2002.1.RUS.RUS6.TVL.NA.31 26 40H0 V 1
#> 1008 2002.4.SWE.77AR.TVL.588.22 25 40G4 V 1
#> 1009 1992.1.DEN.26D4.GRT.54.38 26 41G8 V 1
#> 1010 1992.1.DEN.26D4.GRT.82.57 25 39G6 V 1
#> 1011 1992.1.GFR.06S1.CHP.2407.48 24 39G3 V 1
#> 1012 1992.1.DEN.26D4.GRT.1.1 24 39G2 V 1
#> 1013 1992.1.GFR.06S1.CHP.25082.44 25 40G5 V 1
#> 1014 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1015 1991.1.DEN.26D4.GRT.30.20 25 40G7 V 1
#> 1016 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1017 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1018 1991.1.DEN.26D4.GRT.80.43 26 41G9 V 1
#> 1019 1991.1.GFR.06S1.CHP.2406.29 24 39G3 V 1
#> 1020 1991.1.GFR.06S1.CHP.2509.35 25 40G6 V 1
#> 1021 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 1022 1991.1.GFR.06S1.CHP.26061.46 26 40G8 V 1
#> 1023 2005.1.DEN.26D4.TVL.53.43 24 39G4 V 1
#> 1024 2005.1.GFR.06SL.TVS.24071.50 24 38G3 V 1
#> 1025 2005.1.DEN.26D4.TVL.95.66 25 39G5 V 1
#> 1026 2005.1.SWE.77AR.TVL.224.32 25 40G6 V 1
#> 1027 2005.4.RUS.RUJB.TVL.36.27 26 39G9 V 1
#> 1028 2009.1.POL.67BC.TVL.25056.16 25 38G5 V 1
#> 1029 2009.1.RUS.RUNT.TVL.57.2 26 38G9 V 3
#> 1030 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 1031 2009.4.DEN.26D4.TVL.250.28 25 38G5 V 1
#> 1032 2009.4.DEN.26D4.TVL.226.23 25 38G5 V 1
#> 1033 2000.1.SWE.77AR.GOV.248.42 28 43G8 V 1
#> 1034 2000.4.DEN.26D4.TVL.50.25 25 40G7 V 1
#> 1035 2000.4.SWE.77AR.GOV.584.18 25 40G5 V 1
#> 1036 2011.1.DEN.26D4.TVL.16.16 25 38G5 V 1
#> 1037 2011.1.DEN.26D4.TVL.140.12 24 39G4 V 1
#> 1038 2011.1.POL.67BC.TVL.25173.19 25 38G5 V 1
#> 1039 1995.1.GFR.06S1.H20.26.4 24 38G3 V 1
#> 1040 1995.1.DEN.26D4.GRT.57.23 26 41G9 V 1
#> 1041 1995.1.DEN.26D4.GRT.76.32 25 40G7 V 1
#> 1042 1995.1.LAT.RUEK.DT.000001.23 26 41H0 V 1
#> 1043 1995.1.LAT.RUEK.DT.000001.10 28 43H0 V 1
#> 1044 1995.1.LAT.RUEK.DT.000001.11 28 43H0 V 1
#> 1045 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 1046 1995.1.DEN.26D4.GRT.61.25 26 39G8 V 1
#> 1047 1995.1.DEN.26D4.GRT.88.34 24 38G4 V 1
#> 1048 1995.4.SWE.77AR.FOT.257.12 28 43G9 V 1
#> 1049 1996.1.DEN.26D4.GRT.133.58 24 38G3 V 1
#> 1050 1996.1.DEN.26D4.GRT.28.15 26 41G8 V 1
#> 1051 1996.1.RUS.RUEK.DT.NA.8 26 38G9 V 1
#> 1052 1996.1.SWE.77AR.FOT.96.45 27 43G7 V 1
#> 1053 1996.1.RUS.RUEK.DT.NA.26 26 39G9 V 1
#> 1054 1996.1.SWE.77AR.FOT.71.20 25 40G6 V 1
#> 1055 1996.1.SWE.77AR.FOT.95.44 27 43G7 V 1
#> 1056 1996.1.SWE.77AR.FOT.58.7 24 39G3 V 1
#> 1057 2010.1.DEN.26D4.TVL.100.1 25 39G6 V 1
#> 1058 2010.1.DEN.26D4.TVL.124.5 25 39G5 V 1
#> 1059 2010.1.RUS.RUNT.TVL.60.23 26 38G9 V 1
#> 1060 2010.4.DEN.26D4.TVL.197.24 25 39G6 V 1
#> 1061 2010.4.DEN.26D4.TVL.124.9 25 38G5 V 1
#> 1062 2008.1.DEN.26D4.TVL.58.43 25 39G7 V 1
#> 1063 2008.1.GFR.06SL.TVS.24107.46 24 39G3 V 1
#> 1064 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 1065 2008.4.SWE.77AR.TVL.717.23 25 40G5 V 1
#> 1066 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 1067 1997.1.DEN.26D4.GRT.18.7 25 40G6 V 1
#> 1068 1997.1.SWE.77AR.FOT.174.1 25 40G5 V 1
#> 1069 1997.1.SWE.77AR.FOT.201.23 26 40G8 V 1
#> 1070 1997.1.SWE.77AR.FOT.227.41 27 43G7 V 1
#> 1071 1997.1.SWE.77AR.FOT.197.19 25 40G7 V 1
#> 1072 1997.4.SWE.77AR.FOT.743.14 25 40G7 V 1
#> 1073 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 1074 1997.4.GFR.06S1.H20.25.71 24 38G3 V 1
#> 1075 2007.1.LTU.LTDA.TVS.Mar.4 26 39H0 V 1
#> 1076 2007.1.POL.67BC.TVL.25060.17 25 38G6 V 3
#> 1077 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 1078 2006.1.DEN.26D4.TVL.2.11 25 39G7 V 1
#> 1079 2006.1.DEN.26D4.TVL.67.36 25 39G5 V 1
#> 1080 2006.1.POL.67BC.TVL.25175.17 25 38G5 V 3
#> 1081 2006.4.DEN.26D4.TVL.53.23 25 40G6 V 1
#> 1082 2006.4.DEN.26D4.TVL.101.1 25 40G4 V 1
#> 1083 1993.1.GFR.06S1.H20.40.12 24 38G3 V 1
#> 1084 1993.1.GFR.06S1.H20.41.13 24 38G3 V 1
#> 1085 1993.1.SWE.77AR.FOT.57.9 25 40G7 V 1
#> 1086 1993.4.SWE.77AR.FOT.252.21 25 41G7 V 1
#> 1087 2001.1.DEN.26D4.TVL.38.19 25 40G7 V 1
#> 1088 2012.1.DEN.26D4.TVL.220.40 25 40G4 V 1
#> 1089 2012.4.DEN.26D4.TVL.40.11 25 39G7 V 1
#> 1090 2013.1.DEN.26D4.TVL.36.30 25 39G5 V 1
#> 1091 1998.1.DEN.26D4.GRT.36.17 25 40G7 V 1
#> 1092 1998.1.POL.67BC.P20.03Mar.13 26 38G9 V 1
#> 1093 1998.1.POL.67BC.P20.03Mar.14 26 38G9 V 1
#> 1094 1998.1.POL.67BC.P20.03Mar.32 26 38G8 V 1
#> 1095 1998.1.SWE.77AR.FOT.191.3 25 40G5 V 1
#> 1096 1998.1.SWE.77AR.FOT.230.31 28 43G9 V 1
#> 1097 1998.1.RUS.RUJB.HAK.NA.35 26 40G9 V 1
#> 1098 2004.4.DEN.26D4.TVL.67.32 24 38G4 V 1
#> 1099 2003.1.RUS.RUNT.TVL.NA.2 26 38G9 V 1
#> 1100 2003.1.RUS.RUNT.TVL.NA.29 26 40G9 V 1
#> 1101 2003.4.SWE.77AR.TVL.733.23 25 41G7 V 1
#> 1102 2003.4.SWE.77AR.TVL.737.27 25 40G7 V 1
#> 1103 2003.4.RUS.RUJB.TVL.NA.64 26 38G9 V 1
#> 1104 1999.1.DEN.26D4.GRT.50.23 25 40G7 V 1
#> 1105 1999.1.GFR.06S1.H20.82.139 25 39G7 V 1
#> 1106 1999.1.LAT.AA36.LBT.000001.16 28 42H0 V 1
#> 1107 1999.4.SWE.77AR.FOT.663.27 26 41G8 V 1
#> 1108 2002.4.DEN.26D4.TVL.13.6 25 39G7 V 1
#> 1109 2002.4.SWE.77AR.TVL.577.15 25 40G7 V 1
#> 1110 2002.4.SWE.77AR.TVL.574.12 25 41G7 V 1
#> 1111 2005.1.DEN.26D4.TVL.108.10 25 39G6 V 1
#> 1112 2005.4.RUS.RUJB.TVL.36.32 26 39G9 V 1
#> 1113 2009.1.DEN.26D4.TVL.120.4 25 39G5 V 1
#> 1114 2009.1.SWE.77AR.TVL.271.54 25 40G4 V 1
#> 1115 2009.1.POL.67BC.TVL.26182.30 26 39G8 V 1
#> 1116 1992.1.GFR.06S1.CHP.2501.47 25 40G5 V 1
#> 1117 1992.1.GFR.06S1.CHP.2509.22 25 40G6 V 1
#> 1118 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1119 1992.1.SWE.77AR.FOT.71.22 27 44G8 V 1
#> 1120 1994.1.SWE.77AR.FOT.55.4 27 43G7 V 1
#> 1121 1994.1.SWE.77AR.FOT.70.19 28 43H0 V 1
#> 1122 1991.1.DEN.26D4.GRT.153.70 25 40G5 V 1
#> 1123 1991.1.DEN.26D4.GRT.55.35 28 43G8 V 1
#> 1124 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1125 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1126 1991.1.DEN.26D4.GRT.80.43 26 41G9 V 1
#> 1127 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 1128 1991.1.LAT.90MX.LBT.000001.11 26 41H0 V 1
#> 1129 1991.1.GFR.06S1.CHP.26073.50 26 39G8 V 1
#> 1130 1991.1.LAT.90MX.LBT.000003.1 28 43H0 V 1
#> 1131 1991.1.LAT.90MX.LBT.000003.6 25 38G5 V 1
#> 1132 1991.1.POL.AA36.P20.01Jan.3 26 37G9 V 3
#> 1133 1991.1.LAT.90MX.LBT.000003.28 28 43H0 V 1
#> 1134 1991.1.POL.AA36.P20.03Mar.19 26 38G8 V 1
#> 1135 2000.1.DEN.26D4.GRT.28.14 25 41G7 V 1
#> 1136 2000.1.DEN.26D4.GRT.80.39 25 39G7 V 1
#> 1137 2000.1.POL.67BC.P20.NA.31 26 37G9 V 1
#> 1138 2000.1.SWE.77AR.GOV.240.37 25 40G7 V 1
#> 1139 2000.4.DEN.26D4.TVL.87.44 26 39G8 V 1
#> 1140 2011.1.DEN.26D4.TVL.113.4 25 39G7 V 1
#> 1141 2011.1.POL.67BC.TVL.25046.18 25 38G5 V 1
#> 1142 1995.1.DEN.26D4.GRT.53.21 26 41G9 V 1
#> 1143 1995.1.LAT.RUEK.DT.000001.19 28 42H0 V 1
#> 1144 1995.1.RUS.RUEK.DT.NA.33 26 40G9 V 1
#> 1145 1995.1.SWE.77AR.GOV.80.28 28 43G8 V 1
#> 1146 1995.1.SWE.77AR.GOV.66.14 26 40G8 V 1
#> 1147 1996.1.DEN.26D4.GRT.31.17 26 41G8 V 1
#> 1148 1996.1.GFR.06S1.H20.38.25 24 38G4 V 1
#> 1149 1996.1.GFR.06S1.H20.43.35 24 38G3 V 1
#> 1150 1996.1.DEN.26D4.GRT.57.31 26 41G9 V 1
#> 1151 1996.1.RUS.RUEK.DT.NA.40 26 40G9 V 1
#> 1152 1996.1.RUS.RUEK.DT.NA.17 26 40G8 V 1
#> 1153 1996.1.POL.67BC.P20.01Jan.32 26 38G8 V 3
#> 1154 1996.4.SWE.77AR.FOT.227.22 26 40G9 V 1
#> 1155 2008.1.GFR.06SL.TVS.24002.19 24 37G2 V 1
#> 1156 2008.1.GFR.06SL.TVS.24183.49 24 38G3 V 1
#> 1157 2008.1.DEN.26D4.TVL.56.42 25 39G7 V 1
#> 1158 2008.1.RUS.RUJB.TVL.49.7 26 39G9 V 1
#> 1159 2008.4.GFR.06SL.TVS.24321.24 24 39G3 V 1
#> 1160 2008.4.RUS.RUJB.TVL.51.28 26 39H0 V 1
#> 1161 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 1162 2010.1.DEN.26D4.TVL.209.22 25 39G7 V 1
#> 1163 2010.1.DEN.26D4.TVL.45.39 25 39G5 V 1
#> 1164 2010.1.POL.67BC.TVL.26087.33 26 38G8 V 1
#> 1165 2006.1.DEN.26D4.TVL.83.45 25 40G6 V 1
#> 1166 2006.1.SWE.77AR.TVL.240.46 25 40G5 V 1
#> 1167 2007.1.DEN.26D4.TVL.24.12 25 39G7 V 1
#> 1168 2007.1.POL.67BC.TVL.26044.3 26 39G8 V 3
#> 1169 2007.4.DEN.26D4.TVL.3.44 25 39G5 V 1
#> 1170 1997.1.POL.67BC.P20.01Jan.13 26 38G9 V 3
#> 1171 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 1172 1997.4.SWE.77AR.FOT.746.17 25 41G7 V 1
#> 1173 1997.4.SWE.77AR.FOT.745.16 25 41G7 V 1
#> 1174 1993.1.DEN.26D4.GRT.11.6 24 39G3 V 1
#> 1175 1993.1.DEN.26D4.GRT.162.72 25 38G5 V 1
#> 1176 1993.1.DEN.26D4.GRT.117.56 26 41G9 V 1
#> 1177 1993.1.GFR.06S1.H20.40.12 24 38G3 V 1
#> 1178 1993.1.GFR.06S1.H20.49.23 24 39G4 V 1
#> 1179 1993.1.GFR.06S1.H20.83.37 25 39G6 V 1
#> 1180 1993.1.SWE.77AR.GOV.85.37 24 38G3 V 1
#> 1181 1993.1.SWE.77AR.FOT.55.7 25 40G7 V 1
#> 1182 1993.1.SWE.77AR.FOT.59.11 25 41G6 V 1
#> 1183 1993.1.SWE.77AR.FOT.67.19 27 44G8 V 1
#> 1184 2012.4.DEN.26D4.TVL.46.14 25 39G7 V 1
#> 1185 2001.1.RUS.RUNT.TVL.NA.8 26 39G9 V 1
#> 1186 2001.1.SWE.77AR.TVL.248.39 27 43G6 V 1
#> 1187 2001.4.DEN.26D4.TVL.62.30 25 39G7 V 1
#> 1188 2001.4.DEN.26D4.TVL.20.10 25 39G6 V 1
#> 1189 2013.1.DEN.26D4.TVL.109.2 25 39G6 V 1
#> 1190 2013.4.GFR.06SL.TVS.24059.40 24 38G2 V 1
#> 1191 2004.1.SWE.77AR.TVL.228.2 25 41G7 V 1
#> 1192 2004.1.RUS.RUNT.TVL.NA.13 26 38G9 V 1
#> 1193 2004.4.DEN.26D4.TVL.30.12 26 40G8 V 1
#> 1194 2004.4.DEN.26D4.TVL.59.27 25 39G6 V 1
#> 1195 2004.4.RUS.RUNT.TVL.NA.60 26 39G9 V 1
#> 1196 1998.1.DEN.26D4.GRT.136.64 26 39G8 V 1
#> 1197 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 1198 1998.1.DEN.26D4.GRT.128.60 26 40G9 V 1
#> 1199 1998.1.POL.67BC.P20.03Mar.14 26 38G9 V 1
#> 1200 1998.1.POL.67BC.P20.01Jan.5 26 38G8 V 3
#> 1201 1998.1.POL.67BC.P20.03Mar.63 25 39G7 V 1
#> 1202 1998.1.POL.67BC.P20.01Jan.46 25 39G7 V 3
#> 1203 1998.1.RUS.RUJB.HAK.NA.28 26 39G9 V 1
#> 1204 1998.1.RUS.RUJB.HAK.NA.27 26 39G9 V 1
#> 1205 1998.4.SWE.77AR.FOT.725.26 28 43H0 V 1
#> 1206 2005.1.SWE.77AR.TVL.233.41 25 40G5 V 1
#> 1207 2005.4.RUS.RUJB.TVL.36.35 26 39H0 V 1
#> 1208 2003.1.GFR.06S1.TVS.24036.24 24 39G3 V 1
#> 1209 2003.1.DEN.26D4.TVL.49.26 25 39G6 V 1
#> 1210 2003.1.DEN.26D4.TVL.33.17 25 39G6 V 1
#> 1211 2003.1.RUS.RUNT.TVL.NA.2 26 38G9 V 1
#> 1212 2003.4.DEN.26D4.TVL.26.12 25 39G7 V 1
#> 1213 2003.4.RUS.RUJB.TVL.NA.54 26 40G9 V 1
#> 1214 2003.4.POL.67BC.TVL.NA.3 26 37G9 V 3
#> 1215 1999.1.DEN.26D4.GRT.8.5 25 40G6 V 1
#> 1216 1999.4.SWE.77AR.FOT.663.27 26 41G8 V 1
#> 1217 2002.1.GFR.06S1.TVS.479.179 24 38G3 V 3
#> 1218 2002.1.RUS.RUS6.TVL.NA.13 26 38G9 V 1
#> 1219 2002.4.DEN.26D4.TVL.45.22 25 39G6 V 1
#> 1220 2002.4.SWE.77AR.TVL.574.12 25 41G7 V 1
#> 1221 2009.4.DEN.26D4.TVL.107.1 25 40G7 V 1
#> 1222 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 1223 2009.4.GFR.06SL.TVS.24288.55 24 39G4 V 1
#> 1224 2009.4.SWE.77AR.TVL.741.29 25 40G4 V 1
#> 1225 2009.4.POL.67BC.TVL.NA.4 26 37G9 V 1
#> 1226 2009.4.POL.67BC.TVL.25453.24 25 38G7 V 1
#> 1227 2009.4.POL.67BC.TVL.NA.27 26 37G9 V 1
#> 1228 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 1229 1994.1.SWE.77AR.FOT.65.14 26 41G8 V 1
#> 1230 1994.1.POL.67BC.P20.Mar.37 25 39G7 V 1
#> 1231 1994.1.SWE.77AR.FOT.70.19 28 43H0 V 1
#> 1232 1994.4.GFR.06S1.H20.28.49 24 38G4 V 1
#> 1233 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 1234 1992.1.DEN.26D4.GRT.64.46 28 43G8 V 1
#> 1235 1992.1.DEN.26D4.GRT.82.57 25 39G6 V 1
#> 1236 1992.1.DEN.26D4.GRT.11.8 25 38G5 V 1
#> 1237 1992.1.DEN.26D4.GRT.78.54 26 39G8 V 1
#> 1238 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 1239 1991.1.DEN.26D4.GRT.49.31 28 42G8 V 1
#> 1240 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1241 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1242 1991.1.DEN.26D4.GRT.69.37 26 41G9 V 1
#> 1243 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 1244 1991.1.GFR.06S1.CHP.2512.38 25 40G6 V 1
#> 1245 1991.1.GFR.06S1.CHP.2602.43 26 41G8 V 1
#> 1246 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 1247 1991.1.GFR.06S1.CHP.26062.47 26 39G8 V 1
#> 1248 1991.1.POL.AA36.P20.01Jan.1 26 38G9 V 3
#> 1249 1991.1.POL.AA36.P20.03Mar.19 26 38G8 V 1
#> 1250 1991.1.LAT.90MX.LBT.000003.15 26 39G9 V 1
#> 1251 2011.1.DEN.26D4.TVL.111.3 25 39G7 V 1
#> 1252 2011.1.RUS.RUJB.TVL.56.24 26 39G9 V 1
#> 1253 2011.1.RUS.RUJB.TVL.56.20 25 40G7 V 1
#> 1254 2011.4.DEN.26D4.TVL.24.30 25 40G4 V 1
#> 1255 2011.4.POL.67BC.TVL.25010.13 25 37G6 V 1
#> 1256 2000.1.DEN.26D4.GRT.14.7 25 40G5 V 1
#> 1257 2000.1.SWE.77AR.GOV.243.40 25 40G7 V 1
#> 1258 2000.4.SWE.77AR.GOV.567.1 25 40G4 V 1
#> 1259 2008.1.GFR.06SL.TVS.24058.53 24 38G2 V 1
#> 1260 2008.1.GFR.06SL.TVS.24210.48 24 39G3 V 1
#> 1261 2008.1.GFR.06SL.TVS.24286.30 24 38G4 V 1
#> 1262 2008.1.DEN.26D4.TVL.8.47 25 39G5 V 1
#> 1263 2008.1.RUS.RUJB.TVL.49.2 26 39H0 V 1
#> 1264 2008.1.LAT.67BC.TVL.1.27 26 41G9 V 1
#> 1265 2008.4.DEN.26D4.TVL.155.10 25 39G7 V 1
#> 1266 2008.4.POL.67BC.TVL.26034.22 26 37G9 V 3
#> 1267 2008.4.POL.67BC.TVL.26037.2 26 38G8 V 3
#> 1268 1995.1.GFR.06S1.H20.22.14 24 38G4 V 1
#> 1269 1995.1.RUS.RUEK.DT.NA.14 26 38G9 V 1
#> 1270 1995.1.POL.67BC.P20.02Feb.90 25 39G7 V 1
#> 1271 1995.1.SWE.77AR.GOV.56.4 24 39G4 V 1
#> 1272 1995.4.SWE.77AR.FOT.257.12 28 43G9 V 1
#> 1273 1995.4.SWE.77AR.FOT.250.5 26 40G8 V 1
#> 1274 2010.1.DEN.26D4.TVL.74.44 25 38G5 V 1
#> 1275 2010.1.DEN.26D4.TVL.175.14 25 40G4 V 1
#> 1276 2010.1.DEN.26D4.TVL.210.23 26 40G8 V 1
#> 1277 2010.1.DEN.26D4.TVL.227.28 25 40G7 V 1
#> 1278 2010.1.RUS.RUNT.TVL.60.10 26 40G8 V 1
#> 1279 2010.1.POL.67BC.TVL.26211.1 26 38G9 V 1
#> 1280 2010.4.DEN.26D4.TVL.78.48 25 39G7 V 1
#> 1281 2010.4.DEN.26D4.TVL.118.5 25 38G5 V 1
#> 1282 2010.4.SWE.77AR.TVL.672.4 25 40G4 V 1
#> 1283 1996.1.DEN.26D4.GRT.61.33 26 40G9 V 1
#> 1284 1996.1.DEN.26D4.GRT.14.7 25 38G5 V 1
#> 1285 1996.1.GFR.06S1.H20.41.31 24 38G3 V 1
#> 1286 1996.1.GFR.06S1.H20.68.87 25 38G5 V 1
#> 1287 1996.1.DEN.26D4.GRT.30.16 26 41G8 V 1
#> 1288 1996.1.RUS.RUEK.DT.NA.8 26 38G9 V 1
#> 1289 1996.1.RUS.RUEK.DT.NA.13 26 39G8 V 1
#> 1290 1996.1.LAT.RUEK.DT.000001.86 26 40G9 V 1
#> 1291 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 1292 1996.1.SWE.77AR.FOT.61.10 25 39G5 V 1
#> 1293 1996.1.SWE.77AR.FOT.69.18 25 40G5 V 1
#> 1294 1996.4.SWE.77AR.FOT.229.24 26 41G8 V 1
#> 1295 1996.4.SWE.77AR.GOV.234.29 27 43G7 V 1
#> 1296 2006.1.DEN.26D4.TVL.46.25 25 39G6 V 1
#> 1297 2006.4.POL.67BC.TVL.25173.13 25 38G5 V 3
#> 1298 2006.4.POL.67BC.TVL.NA.29 25 39G7 V 3
#> 1299 2006.4.DEN.26D4.TVL.7.32 25 38G5 V 1
#> 1300 2007.1.DEN.26D4.TVL.108.5 25 38G5 V 1
#> 1301 2007.1.DEN.26D4.TVL.12.6 25 39G7 V 1
#> 1302 2007.1.RUS.RUNT.TVL.52.3 26 38G9 V 1
#> 1303 2007.1.RUS.RUNT.TVL.52.14 26 39H0 V 1
#> 1304 2007.1.POL.67BC.TVL.26015.34 26 37G9 V 3
#> 1305 2007.4.POL.67BC.TVL.25212.15 25 39G6 V 3
#> 1306 2007.4.POL.67BC.TVL.25177.29 25 38G5 V 3
#> 1307 1997.1.POL.67BC.P20.01Jan.13 26 38G9 V 3
#> 1308 1997.1.DEN.26D4.GRT.20.8 25 40G7 V 1
#> 1309 1997.1.SWE.77AR.FOT.198.20 25 41G7 V 1
#> 1310 1997.1.SWE.77AR.FOT.216.32 28 43G8 V 1
#> 1311 1997.1.SWE.77AR.FOT.224.40 27 43G7 V 1
#> 1312 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 1313 1997.4.SWE.77AR.FOT.738.9 25 39G6 V 1
#> 1314 1997.4.LAT.AA36.LBT.2.11 26 41G9 V 1
#> 1315 2012.4.DEN.26D4.TVL.42.12 25 39G7 V 1
#> 1316 2001.1.DEN.26D4.TVL.34.17 25 40G7 V 1
#> 1317 2001.1.RUS.RUNT.TVL.NA.36 26 40H0 V 1
#> 1318 2001.4.DEN.26D4.TVL.73.34 26 39G8 V 1
#> 1319 1993.1.DEN.26D4.GRT.159.69 25 38G5 V 1
#> 1320 1993.1.GFR.06S1.H20.40.12 24 38G3 V 1
#> 1321 1993.1.GFR.06S1.H20.51.19 24 39G3 V 1
#> 1322 1993.1.DEN.26D4.GRT.79.37 26 41G8 V 1
#> 1323 1993.1.SWE.77AR.GOV.53.5 25 40G6 V 1
#> 1324 2004.4.RUS.RUNT.TVL.NA.62 26 39H0 V 1
#> 1325 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 1326 1998.1.DEN.26D4.GRT.128.60 26 40G9 V 1
#> 1327 1998.1.DEN.26D4.GRT.114.53 26 41H0 V 1
#> 1328 1998.1.POL.67BC.P20.03Mar.14 26 38G9 V 1
#> 1329 1998.1.POL.67BC.P20.01Jan.22 26 38G8 V 3
#> 1330 1998.1.POL.67BC.P20.03Mar.63 25 39G7 V 1
#> 1331 1998.1.SWE.77AR.FOT.249.45 25 40G6 V 1
#> 1332 1998.1.SWE.77AR.FOT.205.13 25 41G7 V 1
#> 1333 1998.1.SWE.77AR.FOT.204.12 25 41G7 V 1
#> 1334 1998.1.RUS.RUJB.HAK.NA.33 26 40G9 V 1
#> 1335 2005.1.POL.67BC.TVL.33.33 26 39G8 V 3
#> 1336 2005.1.RUS.RUNT.TVL.NA.49 26 40G8 V 1
#> 1337 2003.1.DEN.26D4.TVL.42.22 25 39G7 V 1
#> 1338 2003.1.DEN.26D4.TVL.77.39 25 39G5 V 1
#> 1339 2009.1.DEN.26D4.TVL.179.15 25 38G5 V 1
#> 1340 2009.1.DEN.26D4.TVL.116.2 25 39G5 V 1
#> 1341 2009.1.GFR.06SL.TVS.24150.33 24 38G4 V 1
#> 1342 2009.1.RUS.RUNT.TVL.57.17 26 39G9 V 3
#> 1343 2009.4.GFR.06SL.TVS.24125.56 24 39G3 V 1
#> 1344 2009.4.DEN.26D4.TVL.133.7 25 39G7 V 1
#> 1345 2009.4.GFR.06SL.TVS.24263.34 24 39G3 V 1
#> 1346 2002.1.DEN.26D4.TVL.109.43 25 40G7 V 1
#> 1347 2002.1.POL.67BC.TVL.7.7 26 38G8 V 3
#> 1348 2002.1.SWE.77AR.TVL.180.5 25 40G7 V 1
#> 1349 1999.1.DEN.26D4.GRT.26.13 25 40G5 V 1
#> 1350 1999.1.DEN.26D4.GRT.52.24 25 40G7 V 1
#> 1351 1999.1.SWE.77AR.FOT.201.10 25 40G6 V 1
#> 1352 1999.1.POL.67BC.P20.03Mar.55 25 39G7 V 1
#> 1353 1999.1.LAT.AA36.LBT.000001.16 28 42H0 V 1
#> 1354 1999.1.SWE.77AR.FOT.207.15 24 39G4 V 1
#> 1355 1999.4.SWE.77AR.FOT.671.33 25 40G5 V 1
#> 1356 1999.4.SWE.77AR.FOT.664.28 26 41G8 V 1
#> 1357 1994.1.GFR.06S1.H20.83.56 25 39G6 V 1
#> 1358 1994.1.DEN.26D4.GRT.1.1 24 39G2 V 1
#> 1359 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 1360 1994.1.SWE.77AR.FOT.60.9 25 40G7 V 1
#> 1361 1994.1.SWE.77AR.FOT.58.7 27 43G7 V 1
#> 1362 1994.1.SWE.77AR.FOT.55.4 27 43G7 V 1
#> 1363 1992.1.DEN.26D4.GRT.56.40 26 41G8 V 1
#> 1364 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1365 1992.1.GFR.06S1.CHP.2810.36 28 42H0 V 1
#> 1366 1992.1.DEN.26D4.GRT.85.59 25 39G5 V 1
#> 1367 1992.1.DEN.26D4.GRT.83.58 25 39G5 V 1
#> 1368 1991.1.DEN.26D4.GRT.15.12 25 38G5 V 1
#> 1369 1991.1.DEN.26D4.GRT.45.29 26 41G8 V 1
#> 1370 1991.1.DEN.26D4.GRT.49.31 28 42G8 V 1
#> 1371 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1372 1991.1.DEN.26D4.GRT.75.40 28 42G9 V 1
#> 1373 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 1374 1991.1.GFR.06S1.CHP.2507.34 25 39G5 V 1
#> 1375 1991.1.GFR.06S1.CHP.25132.40 25 41G7 V 1
#> 1376 1991.1.GFR.06S1.CHP.25151.51 25 39G7 V 1
#> 1377 1991.1.GFR.06S1.CHP.2517.55 25 39G6 V 1
#> 1378 1991.1.LAT.90MX.LBT.000001.17 26 39G9 V 1
#> 1379 1991.1.POL.AA36.P20.01Jan.35 26 38G8 V 3
#> 1380 2011.1.DEN.26D4.TVL.66.49 25 39G6 V 1
#> 1381 2011.1.DEN.26D4.TVL.151.13 25 39G5 V 1
#> 1382 2011.4.POL.67BC.TVL.25051.16 25 38G5 V 1
#> 1383 2000.1.SWE.77AR.GOV.251.45 27 43G7 V 1
#> 1384 2000.1.SWE.77AR.GOV.238.35 25 40G5 V 1
#> 1385 2000.4.DEN.26D4.TVL.87.44 26 39G8 V 1
#> 1386 2008.1.DEN.26D4.TVL.189.24 24 39G4 V 1
#> 1387 2008.1.DEN.26D4.TVL.2.27 25 39G5 V 1
#> 1388 2008.4.LTU.LTDA.TVS.26057.5 26 40G9 V 1
#> 1389 2008.4.DEN.26D4.TVL.155.10 25 39G7 V 1
#> 1390 2008.4.POL.67BC.TVL.26183.1 26 38G8 V 3
#> 1391 2008.4.POL.67BC.TVL.26020.18 26 38G8 V 3
#> 1392 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 1393 2008.4.SWE.77AR.TVL.730.32 25 40G4 V 1
#> 1394 2010.1.DEN.26D4.TVL.173.13 25 40G4 V 1
#> 1395 2010.1.DEN.26D4.TVL.207.20 25 39G7 V 1
#> 1396 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 1397 2010.1.GFR.06SL.TVS.24104.22 24 39G3 V 1
#> 1398 2010.1.RUS.RUNT.TVL.60.16 26 39G8 V 1
#> 1399 2010.1.RUS.RUNT.TVL.60.18 26 39G8 V 1
#> 1400 2010.1.RUS.RUNT.TVL.60.34 26 39H0 V 1
#> 1401 2010.4.DEN.26D4.TVL.221.29 25 40G6 V 1
#> 1402 2010.4.RUS.RUJB.TVL.55.6 26 38G9 V 1
#> 1403 2010.4.SWE.77AR.TVL.673.5 25 40G4 V 1
#> 1404 2006.1.DEN.26D4.TVL.30.16 25 39G7 V 1
#> 1405 2006.4.POL.67BC.TVL.NA.27 25 39G7 V 3
#> 1406 2006.4.POL.67BC.TVL.25180.16 25 38G5 V 3
#> 1407 2007.1.DEN.26D4.TVL.24.12 25 39G7 V 1
#> 1408 2007.1.RUS.RUNT.TVL.52.3 26 38G9 V 1
#> 1409 2007.1.POL.67BC.TVL.25394.29 25 38G5 V 3
#> 1410 2007.4.GFR.06SL.TVS.24210.26 24 39G3 V 1
#> 1411 2007.4.POL.67BC.TVL.25453.10 25 38G7 V 3
#> 1412 2019.4.GFR.06SL.TVS.24171.50 24 38G3 V 1
#> 1413 1995.1.DEN.26D4.GRT.33.14 26 41G8 V 1
#> 1414 1995.1.LAT.RUEK.DT.000001.10 28 43H0 V 1
#> 1415 1995.1.SWE.77AR.GOV.92.40 27 44G8 V 1
#> 1416 1995.1.RUS.RUEK.DT.NA.1 26 40G9 V 1
#> 1417 1995.1.RUS.RUEK.DT.NA.12 26 39G9 V 1
#> 1418 1995.4.SWE.77AR.FOT.265.20 25 40G7 V 1
#> 1419 1995.4.SWE.77AR.FOT.252.7 26 41G8 V 1
#> 1420 1995.4.GFR.06S1.H20.26.46 24 38G3 V 1
#> 1421 1995.4.SWE.77AR.FOT.254.9 28 43G8 V 1
#> 1422 1995.4.SWE.77AR.FOT.246.1 25 40G5 V 1
#> 1423 1995.4.SWE.77AR.FOT.261.16 27 43G7 V 1
#> 1424 1995.4.SWE.77AR.FOT.250.5 26 40G8 V 1
#> 1425 1996.1.GFR.06S1.H20.28.23 24 38G4 V 1
#> 1426 1996.1.GFR.06S1.H20.32.7 24 38G3 V 1
#> 1427 1996.1.GFR.06S1.H20.34.11 24 38G3 V 1
#> 1428 1996.1.RUS.RUEK.DT.NA.18 26 40G8 V 1
#> 1429 1996.1.SWE.77AR.FOT.93.42 27 43G7 V 1
#> 1430 1996.1.SWE.77AR.FOT.95.44 27 43G7 V 1
#> 1431 1996.1.SWE.77AR.FOT.90.39 28 43G8 V 1
#> 1432 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 1433 1996.4.SWE.77AR.GOV.234.29 27 43G7 V 1
#> 1434 1996.4.SWE.77AR.FOT.216.11 25 40G4 V 1
#> 1435 2016.4.GFR.06SL.TVS.24016.18 24 38G2 V 1
#> 1436 1997.1.POL.67BC.P20.01Jan.13 26 38G9 V 3
#> 1437 1997.1.POL.67BC.P20.01Jan.20 26 38G8 V 3
#> 1438 1997.1.POL.67BC.P20.03Mar.18 26 38G9 V 1
#> 1439 1997.4.SWE.77AR.FOT.743.14 25 40G7 V 1
#> 1440 1997.4.SWE.77AR.FOT.768.35 27 43G6 V 1
#> 1441 2001.1.GFR.06S1.TVS.662.41 24 38G3 V 3
#> 1442 2001.1.SWE.77AR.TVL.247.38 27 43G7 V 1
#> 1443 2001.1.RUS.RUNT.TVL.NA.56 28 42H0 V 1
#> 1444 2001.1.SWE.77AR.TVL.204.1 24 39G4 V 1
#> 1445 2001.4.SWE.77AR.TVL.610.18 25 41G7 V 1
#> 1446 2001.4.SWE.77AR.TVL.624.27 25 40G5 V 1
#> 1447 2001.4.SWE.77AR.TVL.627.29 25 40G6 V 1
#> 1448 1993.1.DEN.26D4.GRT.41.19 25 40G6 V 1
#> 1449 2004.4.DEN.26D4.TVL.28.11 26 39G8 V 1
#> 1450 2004.4.RUS.RUNT.TVL.NA.66 26 38G9 V 1
#> 1451 2005.1.DEN.26D4.TVL.51.42 24 39G4 V 1
#> 1452 2005.1.GFR.06SL.TVS.24286.44 24 38G4 V 1
#> 1453 2005.1.RUS.RUNT.TVL.NA.52 26 39G8 V 1
#> 1454 2005.4.SWE.77AR.TVL.612.13 27 42G6 V 1
#> 1455 2005.4.RUS.RUJB.TVL.36.32 26 39G9 V 1
#> 1456 2005.4.POL.67BC.TVL.NA.13 25 38G5 V 3
#> 1457 1998.1.GFR.06S1.H20.66.69 25 41G7 V 1
#> 1458 1998.1.DEN.26D4.GRT.128.60 26 40G9 V 1
#> 1459 1998.1.DEN.26D4.GRT.118.55 26 41G9 V 1
#> 1460 1998.1.POL.67BC.P20.01Jan.17 26 38G8 V 3
#> 1461 1998.1.SWE.77AR.FOT.231.32 28 43G8 V 1
#> 1462 1998.1.RUS.RUJB.HAK.NA.37 26 40H0 V 1
#> 1463 1998.4.SWE.77AR.FOT.703.9 25 40G6 V 1
#> 1464 1998.4.GFR.06S1.H20.29.68 24 38G4 V 1
#> 1465 2009.1.GFR.06SL.TVS.24283.37 24 38G4 V 1
#> 1466 2009.1.DEN.26D4.TVL.116.2 25 39G5 V 1
#> 1467 2009.1.RUS.RUNT.TVL.57.15 26 39G9 V 3
#> 1468 2009.4.DEN.26D4.TVL.111.3 26 40G8 V 1
#> 1469 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 1470 2009.4.DEN.26D4.TVL.137.9 25 39G7 V 1
#> 1471 2009.4.DEN.26D4.TVL.199.17 25 39G6 V 1
#> 1472 2003.1.DEN.26D4.TVL.86.44 25 39G6 V 1
#> 1473 2003.4.DEN.26D4.TVL.49.24 25 39G5 V 1
#> 1474 2003.4.RUS.RUJB.TVL.NA.57 26 39H0 V 1
#> 1475 2002.1.POL.67BC.TVL.20.20 26 39G8 V 3
#> 1476 1999.1.DEN.26D4.GRT.2.2 24 39G2 V 1
#> 1477 1999.1.DEN.26D4.GRT.99.46 26 39G8 V 1
#> 1478 1994.1.DEN.26D4.GRT.2.2 24 39G2 V 1
#> 1479 1994.1.SWE.77AR.FOT.56.5 27 43G7 V 1
#> 1480 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 1481 1994.1.SWE.77AR.GOV.83.32 24 39G4 V 1
#> 1482 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 1483 1992.1.GFR.06S1.CHP.2516.18 25 39G6 V 1
#> 1484 1992.1.DEN.26D4.GRT.61.44 28 42G8 V 1
#> 1485 1992.1.GFR.06S1.CHP.26011.28 26 41G8 V 1
#> 1486 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1487 1992.1.GFR.06S1.CHP.2810.36 28 42H0 V 1
#> 1488 1992.1.SWE.77AR.GOV.87.38 25 40G5 V 1
#> 1489 1992.1.SWE.77AR.FOT.71.22 27 44G8 V 1
#> 1490 1992.1.SWE.77AR.GOV.88.39 25 40G6 V 1
#> 1491 1992.1.SWE.77AR.GOV.58.9 24 39G4 V 1
#> 1492 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 1493 2011.1.DEN.26D4.TVL.87.54 25 39G6 V 1
#> 1494 2011.1.GFR.06SL.TVS.24324.48 24 39G4 V 1
#> 1495 2011.1.POL.67BC.TVL.26182.32 26 39G8 V 1
#> 1496 2011.1.POL.67BC.TVL.25173.19 25 38G5 V 1
#> 1497 2011.4.DEN.26D4.TVL.175.16 25 39G6 V 1
#> 1498 2014.4.DEN.26D4.TVL.74.14 26 39G8 V 1
#> 1499 2008.1.GFR.06SL.TVS.24306.25 24 38G3 V 1
#> 1500 2008.1.GFR.06SL.TVS.24316.41 24 39G4 V 1
#> 1501 2008.1.DEN.26D4.TVL.30.35 25 39G7 V 1
#> 1502 2008.1.POL.67BC.TVL.25061.15 25 38G6 V 3
#> 1503 2008.1.SWE.77AR.TVL.243.48 25 40G6 V 1
#> 1504 2008.4.POL.67BC.TVL.26132.24 26 38G8 V 3
#> 1505 2008.4.POL.67BC.TVL.26182.14 26 39G8 V 3
#> 1506 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 1507 1991.1.DEN.26D4.GRT.36.24 25 41G7 V 1
#> 1508 1991.1.DEN.26D4.GRT.50.32 28 42G8 V 1
#> 1509 1991.1.DEN.26D4.GRT.71.39 26 41H0 V 1
#> 1510 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1511 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1512 1991.1.GFR.06S1.CHP.2604.44 26 41G8 V 1
#> 1513 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 1514 1991.1.LAT.90MX.LBT.000003.19 26 39G9 V 1
#> 1515 1991.1.LAT.90MX.LBT.000003.21 26 39G9 V 1
#> 1516 1991.1.POL.AA36.P20.01Jan.3 26 37G9 V 3
#> 1517 2000.4.SWE.77AR.GOV.589.23 25 40G5 V 1
#> 1518 2010.1.DEN.26D4.TVL.100.1 25 39G6 V 1
#> 1519 2010.1.DEN.26D4.TVL.74.44 25 38G5 V 1
#> 1520 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 1521 2010.1.DEN.26D4.TVL.214.25 26 39G8 V 1
#> 1522 2010.1.DEN.26D4.TVL.45.39 25 39G5 V 1
#> 1523 2010.1.RUS.RUNT.TVL.60.18 26 39G8 V 1
#> 1524 2010.1.POL.67BC.TVL.26087.33 26 38G8 V 1
#> 1525 2010.1.LAT.67BC.TVL.1.30 26 40G9 V 1
#> 1526 2010.4.DEN.26D4.TVL.78.48 25 39G7 V 1
#> 1527 2010.4.DEN.26D4.TVL.118.5 25 38G5 V 1
#> 1528 2010.4.DEN.26D4.TVL.57.45 25 39G7 V 1
#> 1529 2010.4.DEN.26D4.TVL.166.16 25 38G5 V 1
#> 1530 2010.4.DEN.26D4.TVL.108.3 25 40G6 V 1
#> 1531 2010.4.RUS.RUJB.TVL.55.17 26 39G9 V 1
#> 1532 2006.4.GFR.06SL.TVS.24147.21 24 39G3 V 1
#> 1533 2006.4.POL.67BC.TVL.NA.26 25 39G7 V 3
#> 1534 2007.1.DEN.26D4.TVL.60.32 24 39G4 V 1
#> 1535 2007.1.GFR.06SL.TVS.24012.26 24 38G4 V 1
#> 1536 2007.1.RUS.RUNT.TVL.52.1 26 39G9 V 1
#> 1537 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 1538 2007.4.DEN.26D4.TVL.3.44 25 39G5 V 1
#> 1539 2007.4.SWE.77AR.TVL.697.22 25 40G4 V 1
#> 1540 1996.1.DEN.26D4.GRT.32.18 26 41G8 V 1
#> 1541 1996.1.DEN.26D4.GRT.46.26 26 41G9 V 1
#> 1542 1996.1.GFR.06S1.H20.27.131 24 38G3 V 1
#> 1543 1996.1.DEN.26D4.GRT.45.25 26 41H0 V 1
#> 1544 1996.1.DEN.26D4.GRT.57.31 26 41G9 V 1
#> 1545 1996.1.RUS.RUEK.DT.NA.18 26 40G8 V 1
#> 1546 1996.1.RUS.RUEK.DT.NA.16 26 39G8 V 1
#> 1547 1996.1.RUS.RUEK.DT.NA.26 26 39G9 V 1
#> 1548 1996.1.SWE.77AR.FOT.95.44 27 43G7 V 1
#> 1549 1996.1.POL.67BC.P20.03Mar.18 26 38G9 V 1
#> 1550 1996.1.SWE.77AR.FOT.57.6 24 39G3 V 1
#> 1551 1996.4.SWE.77AR.FOT.224.19 25 40G7 V 1
#> 1552 1996.4.SWE.77AR.GOV.235.30 27 43G7 V 1
#> 1553 1995.1.DEN.26D4.GRT.8.2 25 39G6 V 1
#> 1554 1995.1.GFR.06S1.H20.45.45 24 39G3 V 1
#> 1555 1995.1.DEN.26D4.GRT.38.16 28 42G8 V 1
#> 1556 1995.1.DEN.26D4.GRT.40.17 28 42G8 V 1
#> 1557 1995.1.LAT.RUEK.DT.000001.19 28 42H0 V 1
#> 1558 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 1559 1995.1.SWE.77AR.GOV.75.23 25 41G7 V 1
#> 1560 1995.1.SWE.77AR.GOV.98.46 24 39G3 V 1
#> 1561 2012.1.DEN.26D4.TVL.89.52 25 39G5 V 1
#> 1562 2012.1.DEN.26D4.TVL.91.53 25 39G6 V 1
#> 1563 2012.4.POL.67BC.TVL.26217.37 26 38G8 V 1
#> 1564 1997.1.DEN.26D4.GRT.51.24 28 42H0 V 1
#> 1565 1997.1.DEN.26D4.GRT.46.21 26 41G9 V 1
#> 1566 1997.1.POL.67BC.P20.02Feb.4 26 37G9 V 1
#> 1567 1997.1.POL.67BC.P20.03Mar.16 26 38G9 V 1
#> 1568 1997.1.SWE.77AR.FOT.214.30 28 44G9 V 1
#> 1569 1997.1.SWE.77AR.FOT.224.40 27 43G7 V 1
#> 1570 1997.1.SWE.77AR.FOT.194.16 25 40G7 V 1
#> 1571 1997.1.SWE.77AR.FOT.196.18 25 40G6 V 1
#> 1572 1997.4.LAT.AA36.LBT.2.20 26 41G9 V 1
#> 1573 2013.1.DEN.26D4.TVL.162.17 25 40G4 V 1
#> 1574 2013.1.POL.67BC.TVL.25054.15 25 38G5 V 1
#> 1575 2001.1.GFR.06S1.TVS.3337.81 24 37G2 V 3
#> 1576 2001.1.DEN.26D4.TVL.84.41 25 39G5 V 1
#> 1577 2001.1.POL.67BC.TVL.21.21 26 38G8 V 1
#> 1578 2001.1.POL.67BC.TVL.35.35 26 37G9 V 1
#> 1579 2001.4.SWE.77AR.TVL.610.18 25 41G7 V 1
#> 1580 2001.4.SWE.77AR.TVL.602.12 27 42G6 V 1
#> 1581 2004.1.DEN.26D4.TVL.22.8 25 40G7 V 1
#> 1582 2004.1.DEN.26D4.TVL.70.34 25 40G7 V 1
#> 1583 2004.1.LAT.AA36.TVS.1.7 26 40H0 V 1
#> 1584 2004.1.POL.67BC.TVL.32.32 25 38G5 V 3
#> 1585 2004.1.SWE.77AR.TVL.260.30 25 40G6 V 1
#> 1586 2004.4.DEN.26D4.TVL.54.25 25 40G6 V 1
#> 1587 2005.1.RUS.RUNT.TVL.NA.11 26 38G9 V 1
#> 1588 2005.1.RUS.RUNT.TVL.NA.23 26 39G9 V 1
#> 1589 2005.4.POL.67BC.TVL.NA.15 25 38G5 V 3
#> 1590 1993.1.GFR.06S1.H20.43.15 24 38G3 V 1
#> 1591 1993.1.GFR.06S1.H20.50.17 24 39G3 V 1
#> 1592 1993.1.SWE.77AR.FOT.57.9 25 40G7 V 1
#> 1593 1993.1.SWE.77AR.FOT.79.31 25 39G6 V 1
#> 1594 1993.1.SWE.77AR.FOT.80.32 25 39G5 V 1
#> 1595 1993.4.GFR.06S1.H20.29.45 24 38G4 V 1
#> 1596 2009.1.DEN.26D4.TVL.120.4 25 39G5 V 1
#> 1597 2009.1.POL.67BC.TVL.25056.16 25 38G5 V 1
#> 1598 2009.1.DEN.26D4.TVL.142.8 25 38G5 V 1
#> 1599 2009.1.RUS.RUNT.TVL.57.3 26 39G9 V 3
#> 1600 2009.1.RUS.RUNT.TVL.57.8 26 39H0 V 3
#> 1601 2009.1.RUS.RUNT.TVL.57.9 26 39H0 V 3
#> 1602 2009.1.RUS.RUNT.TVL.57.20 26 41G8 V 3
#> 1603 2009.1.POL.67BC.TVL.26137.28 26 40G8 V 1
#> 1604 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 1605 2009.4.SWE.77AR.TVL.737.25 25 40G4 V 1
#> 1606 2009.4.POL.67BC.TVL.26186.2 26 37G9 V 1
#> 1607 1998.1.DEN.26D4.GRT.122.57 26 40G9 V 1
#> 1608 1998.1.DEN.26D4.GRT.44.21 25 41G7 V 1
#> 1609 1998.1.DEN.26D4.GRT.114.53 26 41H0 V 1
#> 1610 1998.1.POL.67BC.P20.01Jan.8 26 38G8 V 3
#> 1611 1998.1.SWE.77AR.FOT.228.29 28 44G9 V 1
#> 1612 1998.1.RUS.RUJB.HAK.NA.27 26 39G9 V 1
#> 1613 1998.4.SWE.77AR.FOT.703.9 25 40G6 V 1
#> 1614 1998.4.SWE.77AR.FOT.704.10 25 40G6 V 1
#> 1615 1998.4.SWE.77AR.FOT.720.22 25 41G7 V 1
#> 1616 1998.4.SWE.77AR.FOT.725.26 28 43H0 V 1
#> 1617 2003.1.DEN.26D4.TVL.77.39 25 39G5 V 1
#> 1618 2003.1.SWE.77AR.TVL.227.8 25 40G5 V 1
#> 1619 2003.1.SWE.77AR.TVL.228.9 25 40G5 V 1
#> 1620 2003.4.DEN.26D4.TVL.32.15 25 40G6 V 1
#> 1621 2003.4.DEN.26D4.TVL.45.22 25 39G6 V 1
#> 1622 2003.4.RUS.RUJB.TVL.NA.56 26 39G9 V 1
#> 1623 2002.1.RUS.RUS6.TVL.NA.32 26 39H0 V 1
#> 1624 2002.1.SWE.77AR.TVL.186.11 25 40G4 V 1
#> 1625 2002.4.DEN.26D4.TVL.45.22 25 39G6 V 1
#> 1626 1999.1.RUS.RUNT.HAK.NA.5 26 38G9 V 1
#> 1627 1999.4.SWE.77AR.FOT.671.33 25 40G5 V 1
#> 1628 1994.1.DEN.26D4.GRT.46.23 26 41G9 V 1
#> 1629 1994.1.SWE.77AR.GOV.83.32 24 39G4 V 1
#> 1630 1994.4.SWE.77AR.FOT.269.14 25 40G7 V 1
#> 1631 1994.4.SWE.77AR.FOT.273.18 27 43G7 V 1
#> 1632 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 1633 1994.4.SWE.77AR.FOT.264.9 24 39G4 V 1
#> 1634 2011.1.DEN.26D4.TVL.113.4 25 39G7 V 1
#> 1635 2011.1.DEN.26D4.TVL.232.30 25 39G5 V 1
#> 1636 2011.1.RUS.RUJB.TVL.56.23 26 39G8 V 1
#> 1637 2011.1.POL.67BC.TVL.26191.4 26 38G9 V 1
#> 1638 1992.1.DEN.26D4.GRT.54.38 26 41G8 V 1
#> 1639 1992.1.GFR.06S1.CHP.2503.15 25 39G5 V 1
#> 1640 1992.1.GFR.06S1.CHP.25081.21 25 40G5 V 1
#> 1641 1992.1.DEN.26D4.GRT.18.13 25 38G5 V 1
#> 1642 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1643 1992.1.GFR.06S1.CHP.28111.37 28 42H0 V 1
#> 1644 1992.1.GFR.06S1.H20.25.31 24 38G3 V 1
#> 1645 1992.1.DEN.26D4.GRT.85.59 25 39G5 V 1
#> 1646 1992.1.SWE.77AR.GOV.85.36 25 40G6 V 1
#> 1647 1992.1.SWE.77AR.FOT.71.22 27 44G8 V 1
#> 1648 2008.1.DEN.26D4.TVL.130.7 25 38G5 V 1
#> 1649 2008.1.DEN.26D4.TVL.28.34 25 39G6 V 1
#> 1650 2008.1.DEN.26D4.TVL.2.27 25 39G5 V 1
#> 1651 2008.1.DEN.26D4.TVL.81.48 25 40G6 V 1
#> 1652 2008.1.SWE.77AR.TVL.249.54 25 40G4 V 1
#> 1653 2008.1.SWE.77AR.TVL.243.48 25 40G6 V 1
#> 1654 2008.4.POL.67BC.TVL.26168.19 26 38G8 V 3
#> 1655 2008.4.LAT.67BC.TVL.2.26 26 40H0 V 1
#> 1656 2008.4.RUS.RUJB.TVL.51.26 26 38G9 V 1
#> 1657 2006.1.RUS.RUJB.TVL.NA.20 26 40G9 V 1
#> 1658 2006.1.POL.67BC.TVL.25175.17 25 38G5 V 3
#> 1659 2006.4.DEN.26D4.TVL.33.12 24 39G4 V 1
#> 1660 2006.4.DEN.26D4.TVL.38.15 25 40G5 V 1
#> 1661 2010.1.DEN.26D4.TVL.74.44 25 38G5 V 1
#> 1662 2010.1.DEN.26D4.TVL.173.13 25 40G4 V 1
#> 1663 2010.1.DEN.26D4.TVL.210.23 26 40G8 V 1
#> 1664 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 1665 2010.1.DEN.26D4.TVL.214.25 26 39G8 V 1
#> 1666 2010.1.RUS.RUNT.TVL.60.18 26 39G8 V 1
#> 1667 2010.1.RUS.RUNT.TVL.60.23 26 38G9 V 1
#> 1668 2010.4.DEN.26D4.TVL.118.5 25 38G5 V 1
#> 1669 2010.4.DEN.26D4.TVL.172.19 25 38G5 V 1
#> 1670 2007.1.DEN.26D4.TVL.67.35 25 39G6 V 1
#> 1671 2007.1.DEN.26D4.TVL.36.18 26 40G8 V 1
#> 1672 2007.1.SWE.77AR.TVL.185.1 25 40G6 V 1
#> 1673 2007.1.RUS.RUNT.TVL.52.3 26 38G9 V 1
#> 1674 2007.1.RUS.RUNT.TVL.52.14 26 39H0 V 1
#> 1675 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 1676 2007.4.SWE.77AR.TVL.697.22 25 40G4 V 1
#> 1677 2007.4.POL.67BC.TVL.25453.10 25 38G7 V 3
#> 1678 2000.1.GFR.06S1.H20.41.44 24 38G3 V 1
#> 1679 2000.1.DEN.26D4.GRT.160.81 25 40G7 V 1
#> 1680 2000.1.DEN.26D4.GRT.30.15 25 40G7 V 1
#> 1681 2000.1.GFR.06S1.H20.42.47 24 38G3 V 1
#> 1682 2000.1.RUS.RUNT.HAK.NA.9 26 39G9 V 1
#> 1683 2000.1.POL.67BC.P20.NA.40 26 37G9 V 1
#> 1684 2000.4.SWE.77AR.GOV.594.27 25 40G7 V 1
#> 1685 2000.4.SWE.77AR.GOV.611.42 27 42G7 V 1
#> 1686 1991.1.DEN.26D4.GRT.40.26 26 41G8 V 1
#> 1687 1991.1.DEN.26D4.GRT.50.32 28 42G8 V 1
#> 1688 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1689 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1690 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 1691 1991.1.DEN.26D4.GRT.83.46 26 40G9 V 1
#> 1692 1991.1.GFR.06S1.CHP.2602.43 26 41G8 V 1
#> 1693 1991.1.LAT.90MX.LBT.000001.11 26 41H0 V 1
#> 1694 1991.1.GFR.06S1.CHP.2604.44 26 41G8 V 1
#> 1695 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 1696 1991.1.GFR.06S1.CHP.2412.80 24 38G3 V 1
#> 1697 2012.1.DEN.26D4.TVL.24.42 24 39G4 V 1
#> 1698 2012.1.DEN.26D4.TVL.89.52 25 39G5 V 1
#> 1699 2012.4.DEN.26D4.TVL.28.9 25 38G6 V 1
#> 1700 1996.1.GFR.06S1.H20.31.21 24 38G4 V 1
#> 1701 1996.1.DEN.26D4.GRT.12.6 25 38G5 V 1
#> 1702 1996.1.GFR.06S1.H20.75.83 25 39G5 V 1
#> 1703 1996.1.DEN.26D4.GRT.28.15 26 41G8 V 1
#> 1704 1996.1.DEN.26D4.GRT.30.16 26 41G8 V 1
#> 1705 1996.1.DEN.26D4.GRT.51.29 26 41G9 V 1
#> 1706 1996.1.DEN.26D4.GRT.40.22 28 43G9 V 1
#> 1707 1996.1.DEN.26D4.GRT.93.44 25 39G5 V 1
#> 1708 1996.1.SWE.77AR.FOT.86.35 28 44G9 V 1
#> 1709 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 1710 1995.1.DEN.26D4.GRT.59.24 26 41H0 V 1
#> 1711 1995.1.GFR.06S1.H20.45.45 24 39G3 V 1
#> 1712 1995.1.GFR.06S1.H20.71.67 25 40G5 V 1
#> 1713 1995.1.DEN.26D4.GRT.40.17 28 42G8 V 1
#> 1714 1995.1.RUS.RUEK.DT.NA.17 26 38G9 V 1
#> 1715 1995.1.SWE.77AR.GOV.90.38 28 44G9 V 1
#> 1716 1995.1.RUS.RUEK.DT.NA.1 26 40G9 V 1
#> 1717 1995.1.RUS.RUEK.DT.NA.2 26 40G9 V 1
#> 1718 1995.4.SWE.77AR.FOT.265.20 25 40G7 V 1
#> 1719 1995.4.GFR.06S1.H20.25.47 24 38G3 V 1
#> 1720 1995.4.SWE.77AR.FOT.257.12 28 43G9 V 1
#> 1721 1995.4.SWE.77AR.FOT.250.5 26 40G8 V 1
#> 1722 1997.1.DEN.26D4.GRT.11.4 25 39G6 V 1
#> 1723 1997.1.DEN.26D4.GRT.32.14 26 41G8 V 1
#> 1724 1997.1.POL.67BC.P20.01Jan.15 26 38G9 V 3
#> 1725 1997.1.POL.67BC.P20.01Jan.14 26 38G9 V 3
#> 1726 1997.1.POL.67BC.P20.03Mar.17 26 38G9 V 1
#> 1727 1997.1.RUS.RUNT.HAK.NA.36 26 40G9 V 1
#> 1728 1997.1.SWE.77AR.FOT.224.40 27 43G7 V 1
#> 1729 1997.1.SWE.77AR.FOT.197.19 25 40G7 V 1
#> 1730 1997.4.SWE.77AR.FOT.756.26 26 41G8 V 1
#> 1731 2001.1.GFR.06S1.TVS.673.66 24 38G3 V 3
#> 1732 2001.1.DEN.26D4.TVL.6.3 24 39G3 V 1
#> 1733 2001.1.DEN.26D4.TVL.110.46 25 38G5 V 1
#> 1734 2001.1.RUS.RUNT.TVL.NA.51 26 41H0 V 1
#> 1735 2001.1.SWE.77AR.TVL.206.3 25 40G4 V 1
#> 1736 2001.1.SWE.77AR.TVL.209.6 25 40G5 V 1
#> 1737 2001.1.SWE.77AR.TVL.251.42 27 43G7 V 1
#> 1738 2001.4.GFR.06S1.TVS.904.47 24 38G3 V 3
#> 1739 2001.4.SWE.77AR.TVL.617.23 25 40G4 V 1
#> 1740 2005.1.SWE.77AR.TVL.233.41 25 40G5 V 1
#> 1741 2005.1.POL.67BC.TVL.33.33 26 39G8 V 3
#> 1742 2005.1.RUS.RUNT.TVL.NA.9 26 38G9 V 1
#> 1743 2005.1.RUS.RUNT.TVL.NA.5 26 39H0 V 1
#> 1744 2005.4.POL.67BC.TVL.NA.30 26 37G9 V 3
#> 1745 2004.1.DEN.26D4.TVL.68.33 25 40G7 V 1
#> 1746 2004.1.RUS.RUNT.TVL.NA.10 26 39G9 V 1
#> 1747 2004.1.RUS.RUNT.TVL.NA.4 26 40G8 V 1
#> 1748 2004.4.DEN.26D4.TVL.22.8 25 39G7 V 1
#> 1749 2004.4.LAT.AA36.TVS.2.2 26 40H0 V 1
#> 1750 2004.4.POL.67BC.TVL.NA.26 25 38G6 V 3
#> 1751 2009.1.DEN.26D4.TVL.220.23 25 39G7 V 1
#> 1752 2009.1.GFR.06SL.TVS.24089.56 24 38G2 V 1
#> 1753 2009.1.GFR.06SL.TVS.24228.20 24 39G3 V 1
#> 1754 2009.1.DEN.26D4.TVL.116.2 25 39G5 V 1
#> 1755 2009.1.GFR.06SL.TVS.24005.50 24 38G2 V 1
#> 1756 2009.1.RUS.RUNT.TVL.57.5 26 39H0 V 3
#> 1757 2009.1.RUS.RUNT.TVL.57.37 26 39G8 V 3
#> 1758 2009.1.RUS.RUNT.TVL.57.34 26 39G8 V 3
#> 1759 2009.1.SWE.77AR.TVL.244.31 25 40G6 V 1
#> 1760 2009.4.DEN.26D4.TVL.131.6 25 39G7 V 1
#> 1761 2009.4.DEN.26D4.TVL.137.9 25 39G7 V 1
#> 1762 2009.4.GFR.06SL.TVS.24288.55 24 39G4 V 1
#> 1763 1993.1.GFR.06S1.H20.82.40 25 39G7 V 1
#> 1764 1993.1.DEN.26D4.GRT.7.4 24 39G3 V 1
#> 1765 1993.1.DEN.26D4.GRT.74.32 26 41G8 V 1
#> 1766 1993.1.SWE.77AR.FOT.63.15 27 43G6 V 1
#> 1767 1993.1.SWE.77AR.FOT.66.18 27 44G8 V 1
#> 1768 1993.4.SWE.77AR.FOT.264.33 25 40G6 V 1
#> 1769 2003.4.DEN.26D4.TVL.55.27 25 40G4 V 1
#> 1770 1998.1.DEN.26D4.GRT.130.61 26 40G9 V 1
#> 1771 1998.1.DEN.26D4.GRT.36.17 25 40G7 V 1
#> 1772 1998.1.RUS.RUJB.HAK.NA.34 26 40G9 V 1
#> 1773 1998.1.POL.67BC.P20.01Jan.48 25 39G7 V 3
#> 1774 1998.1.POL.67BC.P20.03Mar.63 25 39G7 V 1
#> 1775 1998.1.POL.67BC.P20.03Mar.64 25 39G7 V 1
#> 1776 1998.1.SWE.77AR.FOT.206.14 25 40G7 V 1
#> 1777 1998.1.SWE.77AR.FOT.217.22 26 41G8 V 1
#> 1778 1998.4.SWE.77AR.FOT.692.1 25 40G4 V 1
#> 1779 2002.1.GFR.06S1.TVS.788.181 24 38G2 V 3
#> 1780 2002.1.SWE.77AR.TVL.194.19 25 40G5 V 1
#> 1781 2002.1.RUS.RUS6.TVL.NA.9 26 39G9 V 1
#> 1782 2002.4.GFR.06S1.TVS.1278.37 25 38G5 V 3
#> 1783 2002.4.DEN.26D4.TVL.33.16 26 40G9 V 1
#> 1784 2002.4.GFR.06S1.TVS.24012.52 24 38G3 V 3
#> 1785 2002.4.DEN.26D4.TVL.10.4 24 39G4 V 1
#> 1786 1999.1.DEN.26D4.GRT.39.18 25 38G5 V 1
#> 1787 1999.1.RUS.RUNT.HAK.NA.5 26 38G9 V 1
#> 1788 1999.1.POL.67BC.P20.02Feb.25 25 38G5 V 1
#> 1789 1999.1.SWE.77AR.FOT.246.52 26 41G8 V 1
#> 1790 1999.4.SWE.77AR.FOT.671.33 25 40G5 V 1
#> 1791 1999.4.LAT.AA36.LBT.2.8 26 41H0 V 1
#> 1792 1999.4.SWE.77AR.FOT.659.24 25 41G7 V 1
#> 1793 1994.1.DEN.26D4.GRT.23.13 28 42G8 V 1
#> 1794 1994.1.SWE.77AR.FOT.76.25 28 43G8 V 1
#> 1795 1994.1.DEN.26D4.GRT.74.39 26 41G8 V 1
#> 1796 1994.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 1797 1994.1.SWE.77AR.FOT.60.9 25 40G7 V 1
#> 1798 1994.1.SWE.77AR.GOV.83.32 24 39G4 V 1
#> 1799 1994.1.POL.67BC.P20.Mar.8 26 38G8 V 1
#> 1800 1994.1.SWE.77AR.FOT.61.10 25 41G7 V 1
#> 1801 1994.4.SWE.77AR.FOT.273.18 27 43G7 V 1
#> 1802 1994.4.SWE.77AR.FOT.283.28 26 41G8 V 1
#> 1803 2011.1.DEN.26D4.TVL.18.19 25 38G5 V 1
#> 1804 2011.1.DEN.26D4.TVL.187.21 25 40G6 V 1
#> 1805 2011.1.GFR.06SL.TVS.24182.25 24 38G3 V 1
#> 1806 2011.1.POL.67BC.TVL.25394.15 25 38G5 V 1
#> 1807 2008.1.DEN.26D4.TVL.111.6 25 39G6 V 1
#> 1808 2008.1.DEN.26D4.TVL.30.35 25 39G7 V 1
#> 1809 2008.1.SWE.77AR.TVL.243.48 25 40G6 V 1
#> 1810 2008.4.GFR.06SL.TVS.24142.28 24 39G4 V 1
#> 1811 2008.4.DEN.26D4.TVL.132.7 24 38G4 V 1
#> 1812 2008.4.RUS.RUJB.TVL.51.28 26 39H0 V 1
#> 1813 2008.4.RUS.RUJB.TVL.51.33 26 39H0 V 1
#> 1814 2008.4.SWE.77AR.TVL.718.24 25 40G4 V 1
#> 1815 2008.4.LAT.67BC.TVL.2.29 26 40H0 V 1
#> 1816 2008.4.RUS.RUJB.TVL.51.27 26 39G9 V 1
#> 1817 2008.4.RUS.RUJB.TVL.51.23 26 39G9 V 1
#> 1818 1992.1.DEN.26D4.GRT.16.12 25 38G5 V 1
#> 1819 1992.1.DEN.26D4.GRT.81.56 25 39G6 V 1
#> 1820 1992.1.DEN.26D4.GRT.52.37 26 41G8 V 1
#> 1821 1992.1.DEN.26D4.GRT.86.60 25 39G5 V 1
#> 1822 1992.1.DEN.26D4.GRT.54.38 26 41G8 V 1
#> 1823 1992.1.DEN.26D4.GRT.22.15 25 38G5 V 1
#> 1824 1992.1.GFR.06S1.CHP.2504.46 25 39G5 V 1
#> 1825 1992.1.GFR.06S1.CHP.2518.16 25 39G6 V 1
#> 1826 1992.1.GFR.06S1.CHP.26012.41 26 41G8 V 1
#> 1827 1992.1.GFR.06S1.CHP.26021.29 26 41G8 V 1
#> 1828 1992.1.DEN.26D4.GRT.85.59 25 39G5 V 1
#> 1829 1992.1.SWE.77AR.GOV.56.7 24 39G3 V 1
#> 1830 2006.1.DEN.26D4.TVL.2.11 25 39G7 V 1
#> 1831 2006.1.DEN.26D4.TVL.49.26 25 38G5 V 1
#> 1832 2006.1.POL.67BC.TVL.25193.8 25 38G5 V 3
#> 1833 2006.4.DEN.26D4.TVL.104.2 24 39G4 V 1
#> 1834 2006.4.DEN.26D4.TVL.81.38 25 40G7 V 1
#> 1835 2006.4.POL.67BC.TVL.26104.3 26 39G8 V 3
#> 1836 2007.1.DEN.26D4.TVL.64.34 25 38G5 V 1
#> 1837 2007.1.DEN.26D4.TVL.24.12 25 39G7 V 1
#> 1838 2007.1.DEN.26D4.TVL.36.18 26 40G8 V 1
#> 1839 2007.4.DEN.26D4.TVL.283.41 25 39G7 V 1
#> 1840 2007.4.SWE.77AR.TVL.695.20 25 40G4 V 1
#> 1841 2010.1.DEN.26D4.TVL.102.2 25 39G6 V 1
#> 1842 2010.1.DEN.26D4.TVL.98.48 25 39G6 V 1
#> 1843 2010.1.DEN.26D4.TVL.207.20 25 39G7 V 1
#> 1844 2010.1.DEN.26D4.TVL.213.24 26 39G8 V 1
#> 1845 2010.1.RUS.RUNT.TVL.60.18 26 39G8 V 1
#> 1846 2010.1.RUS.RUNT.TVL.60.23 26 38G9 V 1
#> 1847 2010.4.DEN.26D4.TVL.78.48 25 39G7 V 1
#> 1848 2010.4.DEN.26D4.TVL.120.7 25 38G6 V 1
#> 1849 2010.4.DEN.26D4.TVL.172.19 25 38G5 V 1
#> 1850 2000.1.GFR.06S1.H20.44.51 24 39G3 V 1
#> 1851 2000.1.SWE.77AR.GOV.243.40 25 40G7 V 1
#> 1852 2000.4.LAT.AA36.LBT.2.4 26 41G9 V 1
#> 1853 2012.1.DEN.26D4.TVL.89.52 25 39G5 V 1
#> 1854 2012.1.POL.67BC.TVL.25193.36 25 38G5 V 1
#> 1855 2012.1.DEN.26D4.TVL.112.2 25 39G6 V 1
#> 1856 2012.4.GFR.06SL.TVS.24078.32 24 38G4 V 1
#> 1857 1991.1.DEN.26D4.GRT.19.14 25 38G5 V 1
#> 1858 1991.1.DEN.26D4.GRT.40.26 26 41G8 V 1
#> 1859 1991.1.DEN.26D4.GRT.49.31 28 42G8 V 1
#> 1860 1991.1.DEN.26D4.GRT.50.32 28 42G8 V 1
#> 1861 1991.1.DEN.26D4.GRT.55.35 28 43G8 V 1
#> 1862 1991.1.DEN.26D4.GRT.72.1 26 41G9 V 1
#> 1863 1991.1.DEN.26D4.GRT.76.41 26 41G9 V 1
#> 1864 1991.1.DEN.26D4.GRT.81.44 26 41G9 V 1
#> 1865 1991.1.GFR.06S1.CHP.2602.43 26 41G8 V 1
#> 1866 1991.1.GFR.06S1.CHP.2604.44 26 41G8 V 1
#> 1867 1991.1.GFR.06S1.CHP.2605.45 26 40G8 V 1
#> 1868 1991.1.GFR.06S1.CHP.26062.47 26 39G8 V 1
#> 1869 1991.1.GFR.06S1.CHP.26071.48 26 38G8 V 1
#> 1870 1991.1.GFR.06S1.CHP.25151.51 25 39G7 V 1
#> 1871 1991.1.LAT.90MX.LBT.000001.16 26 39G9 V 1
#> 1872 1991.1.GFR.06S1.CHP.25252.64 24 38G4 V 1
#> 1873 1991.1.GFR.06S1.CHP.25223.76 25 38G5 V 1
#> 1874 1991.1.GFR.06S1.CHP.25224.77 25 38G5 V 1
#> 1875 1991.1.GFR.06S1.CHP.2411.79 24 38G3 V 1
#> 1876 1991.1.LAT.90MX.LBT.000003.30 28 43H0 V 1
#> 1877 1991.1.POL.AA36.P20.01Jan.1 26 38G9 V 3
#> 1878 1991.1.LAT.90MX.LBT.000003.28 28 43H0 V 1
#> 1879 1991.1.POL.AA36.P20.03Mar.19 26 38G8 V 1
#> 1880 1991.1.POL.AA36.P20.03Mar.11 26 38G8 V 1
#> 1881 1991.1.LAT.90MX.LBT.000003.11 25 38G5 V 1
#> 1882 1991.1.LAT.90MX.LBT.000003.13 25 38G5 V 1
#> 1883 1991.1.LAT.90MX.LBT.000003.15 26 39G9 V 1
#> 1884 1996.1.DEN.26D4.GRT.22.12 25 40G6 V 1
#> 1885 1996.1.DEN.26D4.GRT.31.17 26 41G8 V 1
#> 1886 1996.1.DEN.26D4.GRT.57.31 26 41G9 V 1
#> 1887 1996.1.DEN.26D4.GRT.30.16 26 41G8 V 1
#> 1888 1996.1.RUS.RUEK.DT.NA.34 26 39G9 V 1
#> 1889 1996.1.RUS.RUEK.DT.NA.17 26 40G8 V 1
#> 1890 1996.1.SWE.77AR.FOT.64.13 25 39G6 V 1
#> 1891 1996.1.SWE.77AR.FOT.100.49 25 40G7 V 1
#> 1892 1996.1.SWE.77AR.FOT.52.1 25 40G4 V 1
#> 1893 1996.1.SWE.77AR.FOT.99.48 25 41G7 V 1
#> 1894 1996.1.SWE.77AR.FOT.78.27 26 41G8 V 1
#> 1895 1996.1.SWE.77AR.FOT.61.10 25 39G5 V 1
#> 1896 2013.4.DEN.26D4.TVL.78.46 25 39G7 V 1
#> 1897 2013.4.DEN.26D4.TVL.82.49 25 39G7 V 1
#> 1898 1995.1.DEN.26D4.GRT.134.49 25 39G6 V 1
#> 1899 1995.1.GFR.06S1.H20.45.45 24 39G3 V 1
#> 1900 1995.1.LAT.RUEK.DT.000001.23 26 41H0 V 1
#> 1901 1995.1.LAT.RUEK.DT.000001.10 28 43H0 V 1
#> 1902 1995.1.LAT.RUEK.DT.000001.21 28 42H0 V 1
#> 1903 1995.1.SWE.77AR.GOV.93.41 27 43G7 V 1
#> 1904 1995.1.SWE.77AR.GOV.94.42 27 43G7 V 1
#> 1905 1995.1.RUS.RUEK.DT.NA.7 26 39G9 V 1
#> 1906 1995.4.SWE.77AR.FOT.266.21 25 40G7 V 1
#> 1907 1995.4.SWE.77AR.FOT.265.20 25 40G7 V 1
#> 1908 1995.4.SWE.77AR.FOT.257.12 28 43G9 V 1
#> 1909 1995.4.SWE.77AR.FOT.250.5 26 40G8 V 1
#> 1910 1997.1.DEN.26D4.GRT.121.52 24 39G3 V 1
#> 1911 1997.1.GFR.06S1.H20.29.29 24 38G4 V 1
#> 1912 1997.1.POL.67BC.P20.01Jan.13 26 38G9 V 3
#> 1913 1997.1.POL.67BC.P20.03Mar.64 25 38G6 V 1
#> 1914 1997.1.POL.67BC.P20.03Mar.23 26 38G8 V 1
#> 1915 1997.1.RUS.RUNT.HAK.NA.36 26 40G9 V 1
#> 1916 1997.1.RUS.RUNT.HAK.NA.16 26 38G9 V 1
#> 1917 1997.1.SWE.77AR.FOT.194.16 25 40G7 V 1
#> 1918 1997.1.SWE.77AR.FOT.195.17 25 40G5 V 1
#> 1919 1997.1.SWE.77AR.FOT.197.19 25 40G7 V 1
#> 1920 1997.4.LAT.AA36.LBT.2.16 28 42H0 V 1
#> 1921 1997.4.SWE.77AR.FOT.743.14 25 40G7 V 1
#> 1922 1997.4.SWE.77AR.FOT.745.16 25 41G7 V 1
#> 1923 1997.4.SWE.77AR.FOT.754.24 26 40G9 V 1
#> BySpecRecCode Fishing.line DataType HaulDur GroundSpeed
#> 1 1 -9.00 R 60 3.0
#> 2 1 -9.00 R 60 3.0
#> 3 1 -9.00 R 60 3.0
#> 4 1 -9.00 R 60 3.0
#> 5 1 -9.00 R 60 3.0
#> 6 1 -9.00 R 60 3.0
#> 7 1 -9.00 R 60 3.0
#> 8 1 -9.00 R 60 3.0
#> 9 1 -9.00 R 60 3.0
#> 10 1 -9.00 R 60 3.0
#> 11 1 -9.00 R 60 3.0
#> 12 1 -9.00 R 60 3.4
#> 13 1 83.00 C 60 3.0
#> 14 1 -9.00 R 60 3.0
#> 15 1 -9.00 C 60 -9.0
#> 16 1 -9.00 R 60 3.6
#> 17 1 83.00 C 30 3.3
#> 18 1 36.00 C 30 4.0
#> 19 1 63.46 R 30 3.0
#> 20 1 28.00 C 30 -9.0
#> 21 1 -9.00 C 60 -9.0
#> 22 1 -9.00 R 60 3.2
#> 23 1 160.00 C 30 3.7
#> 24 1 63.46 R 30 3.1
#> 25 1 -9.00 R 60 3.3
#> 26 1 35.20 C 60 3.5
#> 27 1 63.46 C 30 3.0
#> 28 1 160.00 C 30 3.5
#> 29 1 160.00 C 30 3.5
#> 30 1 -9.00 C 60 -9.0
#> 31 1 -9.00 R 60 3.5
#> 32 1 83.00 C 30 3.3
#> 33 1 83.00 C 30 3.7
#> 34 1 160.00 C 30 3.3
#> 35 1 83.00 C 30 3.3
#> 36 1 -9.00 C 60 -9.0
#> 37 1 -9.00 R 60 3.1
#> 38 1 63.46 C 30 3.0
#> 39 1 -9.00 R 60 -9.0
#> 40 1 33.22 R 30 3.2
#> 41 1 35.20 C 60 3.4
#> 42 1 35.20 C 60 3.5
#> 43 1 -9.00 C 60 -9.0
#> 44 1 83.00 C 30 3.4
#> 45 1 36.00 C 30 3.8
#> 46 1 63.46 R 30 3.0
#> 47 1 83.00 C 60 3.5
#> 48 1 63.46 R 30 3.0
#> 49 1 28.00 C 60 -9.0
#> 50 1 -9.00 C 59 -9.0
#> 51 1 28.00 C 60 -9.0
#> 52 1 83.00 C 30 3.0
#> 53 0 63.46 C 30 3.0
#> 54 1 -9.00 C 30 3.6
#> 55 1 -9.00 C 30 3.6
#> 56 1 63.46 R 30 2.9
#> 57 1 -9.00 C 60 -9.0
#> 58 1 63.46 R 31 2.9
#> 59 1 -9.00 C 30 3.0
#> 60 1 -9.00 R 60 -9.0
#> 61 1 63.46 R 30 3.0
#> 62 1 -9.00 R 60 2.9
#> 63 1 -9.00 R 60 3.1
#> 64 1 83.00 C 30 3.4
#> 65 0 63.46 C 30 -9.0
#> 66 1 160.00 C 60 2.9
#> 67 1 83.00 C 30 3.5
#> 68 1 -9.00 R 60 -9.0
#> 69 1 63.46 C 30 2.9
#> 70 1 63.46 C 30 3.0
#> 71 1 35.20 C 60 3.4
#> 72 1 36.00 C 30 3.4
#> 73 1 83.00 C 30 3.2
#> 74 1 160.00 C 30 3.5
#> 75 0 63.46 C 30 -9.0
#> 76 1 -9.00 C 60 3.9
#> 77 1 -9.00 R 60 -9.0
#> 78 1 36.00 C 30 3.2
#> 79 1 -9.00 R 60 3.0
#> 80 1 83.00 C 30 3.8
#> 81 1 63.46 C 30 3.0
#> 82 1 -9.00 R 60 3.3
#> 83 1 83.00 C 30 3.3
#> 84 1 28.00 C 30 -9.0
#> 85 1 63.46 C 15 3.0
#> 86 1 -9.00 R 60 3.2
#> 87 1 -9.00 C 30 3.3
#> 88 1 -9.00 C 60 -9.0
#> 89 0 39.80 C 30 -9.0
#> 90 1 -9.00 R 60 3.3
#> 91 1 -9.00 C 30 3.5
#> 92 1 36.00 C 30 3.6
#> 93 1 33.22 C 30 3.2
#> 94 1 63.46 R 30 2.8
#> 95 1 63.46 R 31 3.3
#> 96 1 63.46 C 30 3.0
#> 97 1 -9.00 C 60 -9.0
#> 98 1 63.46 C 30 3.0
#> 99 1 63.46 R 29 1.7
#> 100 1 36.00 C 30 4.0
#> 101 1 83.00 C 30 3.5
#> 102 1 36.00 C 30 -9.0
#> 103 1 -9.00 C 60 -9.0
#> 104 1 35.20 C 60 3.5
#> 105 0 39.80 C 30 -9.0
#> 106 1 28.00 C 30 -9.0
#> 107 1 83.00 C 30 3.6
#> 108 1 160.00 C 30 3.7
#> 109 1 63.46 C 31 3.0
#> 110 1 63.46 C 30 3.2
#> 111 0 63.46 C 30 3.0
#> 112 0 63.46 C 30 3.0
#> 113 1 63.46 C 30 3.0
#> 114 1 -9.00 C 60 -9.0
#> 115 1 35.20 C 60 3.5
#> 116 1 160.00 C 60 3.2
#> 117 1 160.00 C 30 3.7
#> 118 1 -9.00 R 60 3.0
#> 119 1 36.00 C 30 3.4
#> 120 1 83.00 C 30 3.3
#> 121 1 63.46 C 30 -9.0
#> 122 0 39.80 C 30 -9.0
#> 123 1 63.46 R 30 3.3
#> 124 0 63.46 C 30 -9.0
#> 125 1 -9.00 C 60 -9.0
#> 126 1 35.20 C 60 3.4
#> 127 1 160.00 C 60 3.2
#> 128 1 -9.00 C 30 3.5
#> 129 1 -9.00 R 30 3.2
#> 130 1 33.22 R 30 3.2
#> 131 1 -9.00 R 60 4.3
#> 132 1 63.46 R 30 3.1
#> 133 1 63.46 R 30 3.0
#> 134 1 36.00 C 30 3.4
#> 135 0 39.80 C 30 -9.0
#> 136 1 35.20 C 60 3.5
#> 137 1 35.20 C 60 3.4
#> 138 1 63.46 R 30 2.9
#> 139 0 39.80 C 30 -9.0
#> 140 1 -9.00 R 60 -9.0
#> 141 1 83.00 C 30 3.9
#> 142 1 63.46 R 30 3.0
#> 143 0 63.46 C 30 -9.0
#> 144 1 -9.00 C 30 3.5
#> 145 1 83.00 C 30 3.5
#> 146 1 63.46 R 30 3.0
#> 147 1 35.20 C 50 3.0
#> 148 1 63.46 R 30 3.3
#> 149 1 -9.00 R 60 3.0
#> 150 1 -9.00 C 30 3.0
#> 151 1 -9.00 R 60 3.7
#> 152 1 83.00 C 30 3.5
#> 153 1 83.00 C 34 3.3
#> 154 1 -9.00 C 30 3.6
#> 155 0 39.80 C 30 -9.0
#> 156 1 -9.00 C 60 3.9
#> 157 1 83.00 C 30 3.7
#> 158 1 83.00 C 30 3.6
#> 159 1 63.46 R 30 3.0
#> 160 1 36.00 C 30 3.8
#> 161 0 39.80 C 30 -9.0
#> 162 1 -9.00 C 60 -9.0
#> 163 0 39.80 C 30 -9.0
#> 164 1 -9.00 C 60 3.9
#> 165 1 160.00 C 30 3.5
#> 166 1 33.22 R 30 3.2
#> 167 1 36.00 C 30 3.8
#> 168 1 83.00 C 30 3.2
#> 169 1 33.22 R 31 3.2
#> 170 1 -9.00 R 60 2.9
#> 171 1 63.46 R 30 2.9
#> 172 1 63.46 R 30 3.0
#> 173 1 33.22 R 30 3.2
#> 174 1 -9.00 C 60 -9.0
#> 175 1 83.00 C 30 3.7
#> 176 1 83.00 C 30 3.5
#> 177 1 28.00 C 30 -9.0
#> 178 1 -9.00 R 60 -9.0
#> 179 1 160.00 C 30 3.4
#> 180 1 -9.00 C 30 3.2
#> 181 1 83.00 C 30 3.6
#> 182 1 -9.00 C 60 -9.0
#> 183 1 35.20 C 60 3.5
#> 184 1 36.00 C 30 4.0
#> 185 1 83.00 C 60 3.2
#> 186 1 63.46 R 30 3.0
#> 187 1 63.46 R 30 3.0
#> 188 1 83.00 C 30 3.2
#> 189 1 63.46 C 30 3.0
#> 190 1 -9.00 R 60 2.9
#> 191 1 160.00 C 30 3.5
#> 192 1 -9.00 R 60 4.0
#> 193 1 -9.00 R 60 3.0
#> 194 1 35.20 C 60 3.2
#> 195 1 35.20 C 60 3.4
#> 196 1 36.00 C 30 3.6
#> 197 1 -9.00 R 60 3.7
#> 198 1 83.00 C 30 3.9
#> 199 1 83.00 C 30 3.5
#> 200 1 33.22 R 30 3.4
#> 201 1 63.46 R 30 2.9
#> 202 1 63.46 R 30 2.9
#> 203 1 -9.00 R 60 3.2
#> 204 0 39.80 C 30 -9.0
#> 205 1 83.00 C 30 3.5
#> 206 1 83.00 C 30 3.7
#> 207 1 83.00 C 30 3.5
#> 208 1 -9.00 R 60 3.1
#> 209 0 39.80 C 30 -9.0
#> 210 1 -9.00 C 60 -9.0
#> 211 1 -9.00 R 60 -9.0
#> 212 1 -9.00 C 60 -9.0
#> 213 1 35.20 C 60 3.5
#> 214 1 35.20 C 60 3.5
#> 215 1 63.46 R 31 3.0
#> 216 1 63.46 R 29 1.7
#> 217 1 33.22 C 30 3.2
#> 218 1 -9.00 C 60 -9.0
#> 219 1 63.46 R 30 3.0
#> 220 1 63.46 R 30 3.0
#> 221 1 63.46 R 30 3.0
#> 222 1 63.46 R 30 3.0
#> 223 1 63.46 R 30 1.7
#> 224 0 63.46 C 30 -9.0
#> 225 1 63.46 C 30 3.0
#> 226 1 28.00 C 30 -9.0
#> 227 1 160.00 C 30 3.5
#> 228 1 83.00 C 30 3.5
#> 229 0 63.46 C 30 -9.0
#> 230 1 63.46 R 30 3.0
#> 231 1 63.46 R 30 2.9
#> 232 1 63.46 R 30 3.0
#> 233 1 63.46 C 30 3.2
#> 234 0 39.80 C 30 -9.0
#> 235 1 -9.00 R 59 3.2
#> 236 1 -9.00 R 59 3.3
#> 237 1 63.46 C 30 -9.0
#> 238 1 63.46 C 21 3.0
#> 239 1 63.46 C 30 3.0
#> 240 1 63.46 R 30 2.9
#> 241 1 36.00 C 30 3.6
#> 242 1 36.00 C 30 3.8
#> 243 1 63.46 R 30 2.9
#> 244 1 33.22 R 30 3.3
#> 245 1 63.46 R 30 2.9
#> 246 1 160.00 C 60 2.9
#> 247 1 83.00 C 60 3.0
#> 248 1 160.00 C 30 3.2
#> 249 1 36.00 C 30 4.0
#> 250 1 35.20 C 60 3.5
#> 251 1 -9.00 R 60 3.0
#> 252 1 36.00 C 30 3.2
#> 253 1 63.46 R 30 3.0
#> 254 1 33.22 R 30 3.0
#> 255 1 -9.00 R 60 3.7
#> 256 1 -9.00 C 30 3.0
#> 257 1 83.00 C 30 3.5
#> 258 1 83.00 C 30 3.5
#> 259 1 28.00 C 60 -9.0
#> 260 1 63.46 C 30 -9.0
#> 261 1 63.46 R 30 3.5
#> 262 0 63.46 C 30 3.0
#> 263 1 160.00 C 60 3.2
#> 264 1 63.46 C 25 3.0
#> 265 1 63.46 C 30 3.1
#> 266 0 63.46 C 30 -9.0
#> 267 1 -9.00 R 60 3.2
#> 268 1 36.00 C 30 3.8
#> 269 1 83.00 C 30 3.3
#> 270 1 -9.00 R 60 3.2
#> 271 1 -9.00 R 60 3.2
#> 272 1 36.00 C 30 3.6
#> 273 1 63.46 C 29 -9.0
#> 274 1 83.00 C 30 3.7
#> 275 1 63.46 C 30 3.0
#> 276 1 63.46 C 30 3.1
#> 277 1 63.46 R 30 3.0
#> 278 1 63.46 R 30 3.0
#> 279 1 63.46 C 30 3.4
#> 280 0 63.46 C 30 -9.0
#> 281 1 -9.00 R 60 -9.0
#> 282 1 -9.00 C 50 -9.0
#> 283 1 83.00 C 30 3.4
#> 284 1 -9.00 C 60 -9.0
#> 285 1 -9.00 C 60 -9.0
#> 286 0 39.80 C 30 -9.0
#> 287 1 -9.00 C 60 -9.0
#> 288 0 39.80 C 30 -9.0
#> 289 1 33.22 R 30 3.2
#> 290 1 63.46 C 30 3.0
#> 291 1 36.00 C 30 -9.0
#> 292 0 63.46 C 30 3.0
#> 293 1 63.46 R 15 2.8
#> 294 1 63.46 R 30 2.9
#> 295 0 39.80 C 30 -9.0
#> 296 1 -9.00 R 60 3.1
#> 297 0 39.80 C 30 -9.0
#> 298 1 28.00 C 60 -9.0
#> 299 1 160.00 C 60 3.2
#> 300 1 83.00 C 30 3.6
#> 301 1 36.00 C 30 3.6
#> 302 1 -9.00 R 59 3.3
#> 303 1 63.46 R 30 2.9
#> 304 1 63.46 C 30 3.0
#> 305 1 63.46 C 30 3.1
#> 306 1 83.00 C 30 3.1
#> 307 1 83.00 C 30 3.2
#> 308 1 83.00 C 30 3.5
#> 309 1 63.46 C 30 2.9
#> 310 1 160.00 C 60 2.9
#> 311 1 160.00 C 60 2.9
#> 312 1 83.00 C 60 2.8
#> 313 1 83.00 C 60 3.0
#> 314 0 63.46 C 30 -9.0
#> 315 0 63.46 C 30 -9.0
#> 316 1 -9.00 C 60 -9.0
#> 317 1 35.20 C 60 3.5
#> 318 1 35.20 C 60 3.5
#> 319 1 36.00 C 30 3.2
#> 320 1 -9.00 R 60 3.0
#> 321 1 160.00 C 30 3.5
#> 322 1 63.46 R 31 2.8
#> 323 1 63.46 C 30 3.2
#> 324 1 36.00 C 30 4.2
#> 325 1 36.00 C 30 -9.0
#> 326 1 -9.00 R 60 3.4
#> 327 1 83.00 C 30 4.0
#> 328 1 83.00 C 30 3.3
#> 329 1 83.00 C 60 3.3
#> 330 1 -9.00 R 60 3.2
#> 331 1 63.46 R 30 3.0
#> 332 1 28.00 C 30 -9.0
#> 333 1 63.46 R 29 1.7
#> 334 1 63.46 R 30 2.9
#> 335 1 63.46 C 30 3.1
#> 336 1 63.46 R 30 3.0
#> 337 1 83.00 C 30 3.2
#> 338 1 83.00 C 30 3.3
#> 339 1 -9.00 C 60 -9.0
#> 340 1 160.00 C 30 3.2
#> 341 1 160.00 C 60 2.9
#> 342 1 160.00 C 60 2.9
#> 343 1 36.00 C 30 4.0
#> 344 0 63.46 C 30 3.0
#> 345 0 63.46 C 30 3.0
#> 346 1 -9.00 R 59 3.0
#> 347 1 160.00 C 30 3.7
#> 348 1 160.00 C 30 3.5
#> 349 1 -9.00 C 60 -9.0
#> 350 1 35.20 C 60 3.5
#> 351 1 63.46 R 30 3.0
#> 352 1 63.46 R 30 3.0
#> 353 1 63.46 R 30 3.0
#> 354 1 63.46 R 31 3.0
#> 355 1 63.46 C 30 3.0
#> 356 1 -9.00 R 60 2.9
#> 357 1 -9.00 R 60 3.0
#> 358 1 -9.00 R 60 3.1
#> 359 1 83.00 C 30 3.6
#> 360 1 -9.00 C 30 3.5
#> 361 1 28.00 C 60 -9.0
#> 362 1 -9.00 R 60 3.2
#> 363 1 -9.00 R 60 3.2
#> 364 1 -9.00 C 30 3.6
#> 365 1 83.00 C 30 3.4
#> 366 0 39.80 C 30 -9.0
#> 367 1 83.00 C 30 3.6
#> 368 1 -9.00 C 30 3.7
#> 369 1 83.00 C 30 3.4
#> 370 1 63.46 R 30 3.1
#> 371 1 63.46 R 30 2.9
#> 372 1 63.46 R 30 3.0
#> 373 1 83.00 C 30 3.3
#> 374 1 83.00 C 30 3.5
#> 375 1 63.46 R 30 3.3
#> 376 1 63.46 R 30 3.4
#> 377 1 63.46 R 30 3.1
#> 378 1 -9.00 C 60 -9.0
#> 379 1 160.00 C 30 3.1
#> 380 1 63.46 C 30 3.1
#> 381 1 33.22 R 30 3.0
#> 382 1 63.46 R 30 3.2
#> 383 1 -9.00 C 30 3.3
#> 384 1 83.00 C 30 3.4
#> 385 1 -9.00 C 60 -9.0
#> 386 1 -9.00 C 59 -9.0
#> 387 0 39.80 C 30 -9.0
#> 388 0 39.80 C 30 -9.0
#> 389 1 83.00 C 60 3.0
#> 390 1 63.46 R 30 3.1
#> 391 1 63.46 R 30 2.9
#> 392 1 -9.00 R 60 3.0
#> 393 1 -9.00 C 30 3.5
#> 394 0 63.46 C 30 -9.0
#> 395 1 63.46 R 30 3.0
#> 396 1 63.46 R 30 2.8
#> 397 1 63.46 C 30 3.0
#> 398 1 63.46 R 30 2.8
#> 399 1 63.46 C 30 3.0
#> 400 1 83.00 C 30 3.4
#> 401 1 -9.00 C 60 -9.0
#> 402 1 28.00 C 30 -9.0
#> 403 1 28.00 C 30 -9.0
#> 404 1 36.00 C 30 -9.0
#> 405 1 -9.00 R 60 3.2
#> 406 0 39.80 C 30 -9.0
#> 407 1 -9.00 C 30 3.5
#> 408 1 28.00 C 60 -9.0
#> 409 1 36.00 C 30 3.4
#> 410 1 63.46 R 30 3.1
#> 411 1 -9.00 R 60 2.7
#> 412 1 36.00 C 30 3.4
#> 413 1 -9.00 R 60 3.2
#> 414 1 83.00 C 30 3.4
#> 415 0 39.80 C 30 -9.0
#> 416 0 39.80 C 30 -9.0
#> 417 1 83.00 C 30 3.5
#> 418 1 63.46 C 30 3.0
#> 419 1 63.46 R 31 3.3
#> 420 1 63.46 R 30 2.8
#> 421 1 33.22 R 30 3.2
#> 422 1 63.46 C 30 3.0
#> 423 1 63.46 C 30 3.1
#> 424 1 63.46 C 30 2.9
#> 425 1 63.46 C 30 3.0
#> 426 1 63.46 C 30 3.0
#> 427 1 63.46 R 30 3.2
#> 428 1 63.46 R 30 3.1
#> 429 1 63.46 R 30 3.3
#> 430 0 63.46 C 30 3.0
#> 431 1 63.46 C 30 3.1
#> 432 1 63.46 C 30 3.2
#> 433 1 -9.00 C 50 -9.0
#> 434 1 -9.00 C 120 3.2
#> 435 1 160.00 C 30 3.4
#> 436 1 33.22 R 30 3.0
#> 437 1 160.00 C 60 2.9
#> 438 1 63.46 R 30 3.0
#> 439 0 63.46 C 30 -9.0
#> 440 1 63.46 R 30 3.3
#> 441 0 63.46 C 30 -9.0
#> 442 0 63.46 C 30 3.0
#> 443 0 63.46 C 30 3.1
#> 444 1 63.46 C 30 3.0
#> 445 1 63.46 R 30 3.0
#> 446 1 160.00 C 30 3.4
#> 447 1 -9.00 R 61 2.9
#> 448 1 -9.00 R 60 3.5
#> 449 1 -9.00 R 60 3.4
#> 450 1 -9.00 C 30 3.0
#> 451 1 83.00 C 30 3.7
#> 452 1 83.00 C 30 3.9
#> 453 1 -9.00 C 60 -9.0
#> 454 1 -9.00 C 60 -9.0
#> 455 1 -9.00 C 60 -9.0
#> 456 1 -9.00 C 60 -9.0
#> 457 1 -9.00 C 60 -9.0
#> 458 1 35.20 C 60 3.5
#> 459 1 35.20 C 60 3.5
#> 460 1 35.20 C 60 3.6
#> 461 1 -9.00 R 60 3.2
#> 462 1 -9.00 R 60 3.6
#> 463 0 39.80 C 30 -9.0
#> 464 1 -9.00 R 60 3.2
#> 465 0 39.80 C 30 -9.0
#> 466 1 83.00 C 30 3.5
#> 467 1 63.46 R 31 3.1
#> 468 1 35.20 C 60 3.4
#> 469 1 35.20 C 60 3.4
#> 470 1 -9.00 R 59 3.5
#> 471 1 -9.00 R 60 3.9
#> 472 1 -9.00 R 60 3.2
#> 473 1 -9.00 C 30 3.9
#> 474 0 39.80 C 30 -9.0
#> 475 1 -9.00 C 30 3.6
#> 476 1 -9.00 C 60 3.9
#> 477 0 39.80 C 30 -9.0
#> 478 1 33.22 R 30 3.2
#> 479 1 33.22 R 30 3.2
#> 480 1 63.46 R 30 3.0
#> 481 1 33.22 R 30 3.2
#> 482 1 33.22 R 30 3.4
#> 483 1 63.46 C 30 3.0
#> 484 1 63.46 R 30 3.3
#> 485 1 63.46 C 30 2.9
#> 486 1 63.46 R 30 2.9
#> 487 1 63.46 C 30 3.0
#> 488 1 63.46 C 30 3.1
#> 489 1 63.46 R 30 3.2
#> 490 1 63.46 R 30 2.9
#> 491 1 63.46 C 30 3.0
#> 492 1 63.46 R 30 3.2
#> 493 1 -9.00 C 60 -9.0
#> 494 1 36.00 C 30 4.0
#> 495 1 160.00 C 30 3.4
#> 496 0 39.80 C 30 -9.0
#> 497 1 63.46 R 30 3.0
#> 498 0 63.46 C 30 3.0
#> 499 0 63.46 C 30 3.0
#> 500 1 63.46 R 30 3.1
#> 501 1 63.46 R 30 2.8
#> 502 1 -9.00 R 60 -9.0
#> 503 1 160.00 C 30 3.7
#> 504 1 63.46 R 30 2.9
#> 505 1 63.46 R 29 3.0
#> 506 1 63.46 C 30 3.1
#> 507 1 63.46 C 30 3.0
#> 508 1 36.00 C 30 3.4
#> 509 1 -9.00 C 30 3.5
#> 510 1 160.00 C 30 3.6
#> 511 1 160.00 C 30 3.6
#> 512 1 36.00 C 30 3.8
#> 513 1 -9.00 C 60 -9.0
#> 514 1 -9.00 C 60 -9.0
#> 515 0 39.80 C 30 -9.0
#> 516 1 -9.00 R 60 3.0
#> 517 1 -9.00 C 30 3.0
#> 518 1 83.00 C 30 3.5
#> 519 0 39.80 C 30 -9.0
#> 520 1 83.00 C 30 3.3
#> 521 1 83.00 C 30 3.5
#> 522 1 -9.00 C 60 -9.0
#> 523 1 35.20 C 60 3.5
#> 524 1 35.20 C 60 3.5
#> 525 0 39.80 C 30 -9.0
#> 526 1 63.46 R 30 3.0
#> 527 1 63.46 R 30 3.1
#> 528 1 63.46 R 29 3.0
#> 529 1 -9.00 C 63 -9.0
#> 530 1 35.20 C 60 3.4
#> 531 1 -9.00 C 60 -9.0
#> 532 1 -9.00 R 60 3.3
#> 533 1 -9.00 R 60 3.2
#> 534 0 39.80 C 30 -9.0
#> 535 1 83.00 C 30 3.3
#> 536 1 83.00 C 30 3.3
#> 537 1 -9.00 C 30 3.6
#> 538 1 36.00 C 30 3.4
#> 539 0 39.80 C 30 -9.0
#> 540 1 63.46 C 30 -9.0
#> 541 1 83.00 C 30 3.5
#> 542 1 33.22 R 30 3.2
#> 543 1 63.46 R 30 3.1
#> 544 1 63.46 R 30 3.0
#> 545 1 63.46 R 30 3.0
#> 546 1 63.46 R 30 2.3
#> 547 1 33.22 R 30 3.2
#> 548 1 63.46 R 31 3.3
#> 549 1 63.46 R 30 3.1
#> 550 1 63.46 C 30 3.0
#> 551 0 63.46 C 30 -9.0
#> 552 1 63.46 R 30 2.8
#> 553 1 33.22 R 30 3.0
#> 554 1 63.46 C 30 3.0
#> 555 1 63.46 C 30 3.1
#> 556 1 63.46 R 30 3.3
#> 557 0 63.46 C 30 -9.0
#> 558 1 63.46 R 30 3.2
#> 559 1 63.46 R 30 3.0
#> 560 0 63.46 C 30 -9.0
#> 561 0 63.46 C 30 -9.0
#> 562 1 33.22 R 30 3.3
#> 563 1 63.46 R 30 3.5
#> 564 1 63.46 C 30 3.1
#> 565 0 63.46 C 30 3.0
#> 566 1 63.46 C 15 -9.0
#> 567 1 33.22 R 30 3.2
#> 568 1 63.46 R 30 2.9
#> 569 1 -9.00 C 60 -9.0
#> 570 0 39.80 C 30 -9.0
#> 571 0 39.80 C 30 -9.0
#> 572 1 63.46 C 30 -9.0
#> 573 1 63.46 R 15 2.8
#> 574 1 63.46 R 30 3.0
#> 575 1 63.46 R 30 2.9
#> 576 1 63.46 C 30 3.0
#> 577 0 63.46 C 30 -9.0
#> 578 0 63.46 C 30 -9.0
#> 579 1 -9.00 R 60 -9.0
#> 580 1 -9.00 C 60 -9.0
#> 581 1 160.00 C 30 3.5
#> 582 1 -9.00 C 30 3.2
#> 583 1 83.00 C 30 3.5
#> 584 1 83.00 C 30 3.4
#> 585 1 63.46 R 30 2.6
#> 586 1 63.46 R 29 3.0
#> 587 1 63.46 R 30 3.0
#> 588 0 63.46 C 30 2.9
#> 589 1 63.46 C 30 3.1
#> 590 1 63.46 R 30 2.8
#> 591 1 63.46 C 30 3.0
#> 592 1 36.00 C 30 3.2
#> 593 1 -9.00 C 30 3.5
#> 594 1 -9.00 C 30 3.2
#> 595 1 -9.00 C 60 -9.0
#> 596 1 -9.00 C 60 -9.0
#> 597 1 28.00 C 60 -9.0
#> 598 1 83.00 C 60 3.3
#> 599 1 -9.00 R 60 3.5
#> 600 1 -9.00 R 60 3.4
#> 601 0 39.80 C 30 -9.0
#> 602 1 -9.00 C 30 3.5
#> 603 1 -9.00 C 25 3.7
#> 604 1 83.00 C 30 3.4
#> 605 1 83.00 C 30 3.5
#> 606 1 63.46 R 30 3.1
#> 607 1 63.46 C 30 3.0
#> 608 1 63.46 R 30 2.9
#> 609 1 -9.00 C 60 -9.0
#> 610 1 -9.00 C 60 -9.0
#> 611 1 -9.00 C 60 -9.0
#> 612 1 35.20 C 60 3.5
#> 613 0 39.80 C 30 -9.0
#> 614 0 39.80 C 30 -9.0
#> 615 1 28.00 C 60 -9.0
#> 616 1 63.46 C 30 3.0
#> 617 1 -9.00 R 60 3.9
#> 618 1 -9.00 R 60 3.4
#> 619 1 -9.00 C 45 3.5
#> 620 1 63.46 R 30 3.0
#> 621 1 160.00 C 60 2.7
#> 622 1 -9.00 R 59 3.0
#> 623 0 63.46 C 30 -9.0
#> 624 1 63.46 R 30 3.3
#> 625 0 63.46 C 30 -9.0
#> 626 0 63.46 C 30 -9.0
#> 627 1 63.46 R 30 3.1
#> 628 1 63.46 C 30 2.9
#> 629 1 63.46 R 30 3.3
#> 630 0 63.46 C 30 3.0
#> 631 1 63.46 R 30 3.1
#> 632 1 63.46 R 30 3.0
#> 633 1 63.46 C 30 3.2
#> 634 0 63.46 C 30 -9.0
#> 635 1 63.46 C 30 3.2
#> 636 1 63.46 C 30 3.2
#> 637 1 63.46 R 30 3.0
#> 638 1 63.46 R 30 3.1
#> 639 1 63.46 R 30 3.3
#> 640 0 63.46 C 30 -9.0
#> 641 0 63.46 C 30 -9.0
#> 642 0 63.46 C 30 -9.0
#> 643 1 33.22 R 30 3.0
#> 644 1 63.46 C 30 -9.0
#> 645 0 63.46 C 30 -9.0
#> 646 1 63.46 C 30 3.0
#> 647 0 63.46 C 30 -9.0
#> 648 1 63.46 C 30 3.0
#> 649 1 63.46 R 29 3.0
#> 650 1 63.46 R 31 2.7
#> 651 1 33.22 R 30 3.3
#> 652 1 -9.00 R 60 -9.0
#> 653 1 -9.00 C 70 -9.0
#> 654 1 160.00 C 30 3.5
#> 655 1 160.00 C 30 3.7
#> 656 1 36.00 C 30 3.6
#> 657 1 83.00 C 60 3.3
#> 658 1 83.00 C 60 3.0
#> 659 1 83.00 C 60 2.9
#> 660 1 -9.00 R 60 3.0
#> 661 1 36.00 C 30 3.0
#> 662 1 -9.00 C 30 3.0
#> 663 1 83.00 C 30 3.6
#> 664 1 -9.00 C 30 -9.0
#> 665 1 83.00 C 30 3.5
#> 666 1 -9.00 R 60 3.0
#> 667 1 83.00 C 30 3.5
#> 668 1 63.46 R 30 3.1
#> 669 1 63.46 C 30 3.0
#> 670 1 33.22 C 30 3.2
#> 671 1 63.46 C 30 2.9
#> 672 1 63.46 R 30 3.0
#> 673 1 63.46 C 30 3.0
#> 674 1 63.46 C 30 2.9
#> 675 1 63.46 C 30 3.0
#> 676 1 63.46 C 30 3.0
#> 677 1 63.46 R 30 3.2
#> 678 1 63.46 R 30 2.1
#> 679 1 63.46 R 30 3.3
#> 680 1 -9.00 C 60 -9.0
#> 681 1 -9.00 C 60 -9.0
#> 682 1 -9.00 C 60 -9.0
#> 683 1 35.20 C 60 3.5
#> 684 1 28.00 C 30 -9.0
#> 685 1 35.20 C 60 3.5
#> 686 1 36.00 C 30 -9.0
#> 687 0 39.80 C 30 -9.0
#> 688 0 39.80 C 30 -9.0
#> 689 1 -9.00 R 60 2.7
#> 690 1 -9.00 R 60 3.9
#> 691 1 36.00 C 30 3.6
#> 692 1 -9.00 R 60 3.4
#> 693 1 83.00 C 30 3.3
#> 694 0 39.80 C 30 -9.0
#> 695 0 39.80 C 30 -9.0
#> 696 1 -9.00 C 30 3.6
#> 697 1 -9.00 C 45 3.5
#> 698 1 63.46 C 30 3.0
#> 699 1 63.46 R 30 3.2
#> 700 0 63.46 C 30 -9.0
#> 701 1 63.46 R 29 3.0
#> 702 1 63.46 R 30 3.1
#> 703 0 63.46 C 30 -9.0
#> 704 1 -9.00 C 63 -9.0
#> 705 1 35.20 C 60 3.4
#> 706 1 35.20 C 60 3.4
#> 707 1 -9.00 C 59 -9.0
#> 708 1 -9.00 C 61 -9.0
#> 709 1 -9.00 C 63 -9.0
#> 710 1 160.00 C 60 3.1
#> 711 1 83.00 C 60 3.2
#> 712 1 160.00 C 60 3.2
#> 713 0 63.46 C 30 3.0
#> 714 1 -9.00 R 60 3.8
#> 715 1 -9.00 R 60 4.1
#> 716 1 36.00 C 30 3.8
#> 717 1 36.00 C 30 3.6
#> 718 1 83.00 C 30 3.5
#> 719 1 160.00 C 30 3.3
#> 720 1 83.00 C 30 3.4
#> 721 1 63.46 C 30 3.1
#> 722 1 63.46 C 30 3.0
#> 723 1 63.46 R 30 3.0
#> 724 1 63.46 R 30 3.0
#> 725 1 -9.00 C 60 -9.0
#> 726 1 -9.00 C 60 -9.0
#> 727 1 83.00 C 30 3.0
#> 728 1 63.46 R 30 3.0
#> 729 1 63.46 C 30 3.1
#> 730 0 63.46 C 30 -9.0
#> 731 0 63.46 C 30 -9.0
#> 732 0 63.46 C 30 -9.0
#> 733 1 63.46 R 30 2.8
#> 734 1 63.46 R 30 3.0
#> 735 1 63.46 R 30 2.9
#> 736 1 33.22 R 30 3.5
#> 737 1 63.46 R 30 3.0
#> 738 0 63.46 C 30 3.0
#> 739 1 63.46 R 30 2.8
#> 740 1 -9.00 C 90 3.3
#> 741 1 -9.00 C 30 3.2
#> 742 1 83.00 C 30 3.7
#> 743 1 -9.00 R 60 2.9
#> 744 1 -9.00 R 29 3.0
#> 745 1 83.00 C 30 3.5
#> 746 1 160.00 C 30 3.6
#> 747 1 -9.00 R 60 3.0
#> 748 1 83.00 C 30 3.8
#> 749 0 39.80 C 30 -9.0
#> 750 0 39.80 C 30 -9.0
#> 751 1 83.00 C 30 3.7
#> 752 1 83.00 C 30 3.6
#> 753 1 83.00 C 30 3.6
#> 754 1 -9.00 C 60 -9.0
#> 755 1 28.00 C 60 -9.0
#> 756 1 28.00 C 60 -9.0
#> 757 0 39.80 C 30 -9.0
#> 758 1 83.00 C 60 3.3
#> 759 1 63.46 R 30 3.1
#> 760 1 63.46 R 31 2.9
#> 761 1 63.46 R 30 2.9
#> 762 1 63.46 R 30 3.0
#> 763 0 39.80 C 30 -9.0
#> 764 0 39.80 C 30 -9.0
#> 765 0 39.80 C 30 -9.0
#> 766 1 -9.00 C 30 3.5
#> 767 1 83.00 C 30 3.1
#> 768 1 83.00 C 30 3.2
#> 769 1 83.00 C 34 3.3
#> 770 1 63.46 R 30 2.0
#> 771 1 63.46 R 30 2.8
#> 772 1 33.22 R 30 3.2
#> 773 1 63.46 C 30 2.9
#> 774 1 63.46 C 30 3.0
#> 775 1 63.46 C 30 3.0
#> 776 1 63.46 R 30 3.4
#> 777 1 63.46 R 30 2.8
#> 778 1 63.46 R 29 3.3
#> 779 1 63.46 R 30 2.9
#> 780 1 63.46 R 30 3.0
#> 781 0 63.46 C 30 -9.0
#> 782 1 63.46 R 30 3.3
#> 783 1 63.46 R 30 3.2
#> 784 1 63.46 R 30 3.0
#> 785 1 63.46 C 30 3.0
#> 786 0 63.46 C 30 3.0
#> 787 1 63.46 C 30 3.1
#> 788 1 33.22 R 30 3.2
#> 789 1 63.46 R 30 2.9
#> 790 1 -9.00 R 60 3.5
#> 791 1 -9.00 C 30 3.6
#> 792 0 39.80 C 30 -9.0
#> 793 1 -9.00 C 30 3.6
#> 794 1 -9.00 C 60 3.9
#> 795 1 -9.00 C 60 -9.0
#> 796 1 -9.00 C 60 -9.0
#> 797 1 -9.00 C 60 -9.0
#> 798 1 -9.00 C 60 -9.0
#> 799 1 35.20 C 60 3.5
#> 800 0 39.80 C 30 -9.0
#> 801 1 28.00 C 30 -9.0
#> 802 1 36.00 C 30 3.0
#> 803 0 39.80 C 30 -9.0
#> 804 1 28.00 C 60 -9.0
#> 805 1 63.46 C 30 -9.0
#> 806 1 83.00 C 30 3.2
#> 807 1 28.00 C 30 -9.0
#> 808 1 28.00 C 30 -9.0
#> 809 1 -9.00 C 61 -9.0
#> 810 1 -9.00 C 60 -9.0
#> 811 1 35.20 C 60 3.5
#> 812 1 83.00 C 60 3.2
#> 813 1 63.46 R 30 3.0
#> 814 1 63.46 R 30 2.9
#> 815 1 63.46 R 30 2.9
#> 816 1 63.46 R 31 2.9
#> 817 1 63.46 R 30 2.9
#> 818 1 63.46 C 30 3.0
#> 819 1 63.46 R 30 3.0
#> 820 0 63.46 C 30 -9.0
#> 821 1 63.46 R 30 3.0
#> 822 1 63.46 R 30 3.0
#> 823 0 63.46 C 30 -9.0
#> 824 1 63.46 C 30 3.1
#> 825 1 63.46 R 30 2.9
#> 826 1 -9.00 C 60 -9.0
#> 827 1 160.00 C 30 3.2
#> 828 1 -9.00 C 60 -9.0
#> 829 1 83.00 C 30 3.0
#> 830 1 83.00 C 30 3.1
#> 831 0 39.80 C 30 -9.0
#> 832 1 83.00 C 30 3.3
#> 833 1 83.00 C 30 3.2
#> 834 1 63.46 R 30 3.0
#> 835 1 63.46 C 30 -9.0
#> 836 1 33.22 R 30 3.7
#> 837 0 63.46 C 30 3.1
#> 838 0 63.46 C 30 3.0
#> 839 0 63.46 C 30 3.0
#> 840 1 63.46 R 30 3.0
#> 841 1 63.46 R 30 2.8
#> 842 1 33.22 R 30 3.4
#> 843 1 63.46 C 30 3.0
#> 844 1 -9.00 R 60 -9.0
#> 845 1 -9.00 R 59 -9.0
#> 846 1 36.00 C 30 4.0
#> 847 1 36.00 C 30 3.2
#> 848 1 -9.00 C 30 3.4
#> 849 1 36.00 C 30 3.2
#> 850 1 160.00 C 30 3.7
#> 851 1 -9.00 R 60 4.0
#> 852 1 -9.00 R 60 3.1
#> 853 0 39.80 C 30 -9.0
#> 854 1 -9.00 C 30 -9.0
#> 855 1 83.00 C 30 3.7
#> 856 1 83.00 C 30 3.6
#> 857 1 63.46 R 31 3.1
#> 858 1 63.46 C 30 3.0
#> 859 1 63.46 C 30 3.0
#> 860 1 63.46 R 30 2.9
#> 861 1 63.46 R 30 3.0
#> 862 1 -9.00 C 59 -9.0
#> 863 1 160.00 C 60 2.9
#> 864 1 -9.00 R 60 3.2
#> 865 0 39.80 C 30 -9.0
#> 866 0 39.80 C 30 -9.0
#> 867 1 -9.00 R 60 3.2
#> 868 1 83.00 C 30 3.0
#> 869 1 83.00 C 30 3.4
#> 870 1 63.46 R 30 3.1
#> 871 1 63.46 R 30 3.0
#> 872 1 63.46 R 30 0.1
#> 873 1 63.46 R 31 3.2
#> 874 1 63.46 C 30 3.0
#> 875 1 63.46 R 25 3.0
#> 876 1 63.46 R 30 3.0
#> 877 1 63.46 R 30 3.2
#> 878 1 63.46 R 30 3.0
#> 879 0 63.46 C 30 -9.0
#> 880 1 33.22 R 30 3.2
#> 881 1 63.46 R 30 3.2
#> 882 1 63.46 C 30 3.0
#> 883 1 63.46 R 30 3.1
#> 884 1 63.46 R 30 3.2
#> 885 0 63.46 C 30 -9.0
#> 886 1 36.00 C 30 3.6
#> 887 1 -9.00 R 60 3.2
#> 888 1 -9.00 R 60 3.5
#> 889 0 39.80 C 30 -9.0
#> 890 1 83.00 C 30 3.7
#> 891 1 -9.00 R 60 3.6
#> 892 1 -9.00 R 60 3.2
#> 893 1 36.00 C 30 3.4
#> 894 1 -9.00 C 30 3.5
#> 895 0 39.80 C 30 -9.0
#> 896 0 39.80 C 30 -9.0
#> 897 1 83.00 C 30 3.4
#> 898 1 -9.00 C 60 -9.0
#> 899 1 35.20 C 60 3.5
#> 900 1 28.00 C 60 -9.0
#> 901 1 35.20 C 60 3.5
#> 902 1 35.20 C 60 3.5
#> 903 1 28.00 C 30 -9.0
#> 904 0 39.80 C 30 -9.0
#> 905 1 28.00 C 30 -9.0
#> 906 0 39.80 C 30 -9.0
#> 907 1 35.20 C 60 3.1
#> 908 1 35.20 C 60 -9.0
#> 909 1 35.20 C 60 3.4
#> 910 1 63.46 R 30 3.0
#> 911 1 63.46 R 30 2.9
#> 912 1 33.22 C 30 3.2
#> 913 1 63.46 C 30 3.0
#> 914 1 63.46 C 30 2.9
#> 915 1 -9.00 C 60 -9.0
#> 916 1 -9.00 C 60 -9.0
#> 917 1 -9.00 C 60 -9.0
#> 918 0 39.80 C 30 -9.0
#> 919 0 39.80 C 30 -9.0
#> 920 1 83.00 C 30 3.2
#> 921 1 33.22 R 30 3.3
#> 922 0 63.46 C 30 -9.0
#> 923 0 63.46 C 30 -9.0
#> 924 1 63.46 C 30 3.1
#> 925 1 63.46 C 30 3.0
#> 926 0 63.46 C 30 -9.0
#> 927 1 63.46 R 30 2.9
#> 928 1 63.46 R 30 2.9
#> 929 0 63.46 C 30 3.1
#> 930 1 63.46 R 30 3.0
#> 931 1 63.46 R 30 2.8
#> 932 1 63.46 R 30 3.1
#> 933 1 63.46 C 30 3.1
#> 934 1 63.46 C 30 3.0
#> 935 1 63.46 C 30 3.0
#> 936 1 -9.00 R 60 3.0
#> 937 0 39.80 C 30 -9.0
#> 938 1 28.00 C 30 -9.0
#> 939 1 -9.00 R 60 -9.0
#> 940 1 -9.00 C 50 -9.0
#> 941 1 -9.00 R 60 -9.0
#> 942 1 160.00 C 30 3.7
#> 943 1 83.00 C 30 3.6
#> 944 1 33.22 R 30 3.2
#> 945 1 63.46 C 30 -9.0
#> 946 1 -9.00 R 60 3.3
#> 947 1 36.00 C 30 3.8
#> 948 1 -9.00 C 30 3.0
#> 949 0 39.80 C 30 -9.0
#> 950 1 83.00 C 30 3.4
#> 951 1 83.00 C 30 3.7
#> 952 1 83.00 C 30 4.0
#> 953 1 28.00 C 60 -9.0
#> 954 1 28.00 C 60 -9.0
#> 955 1 83.00 C 30 3.4
#> 956 1 83.00 C 30 3.5
#> 957 1 36.00 C 30 3.6
#> 958 1 160.00 C 60 2.9
#> 959 1 83.00 C 60 2.8
#> 960 1 83.00 C 60 3.5
#> 961 1 83.00 C 60 3.0
#> 962 1 63.46 R 30 3.0
#> 963 1 63.46 R 30 3.0
#> 964 1 33.22 R 30 3.3
#> 965 1 63.46 C 30 3.0
#> 966 1 63.46 C 15 3.0
#> 967 1 63.46 C 30 3.0
#> 968 1 63.46 R 31 3.2
#> 969 1 63.46 R 30 3.4
#> 970 1 63.46 R 30 2.1
#> 971 1 63.46 C 30 3.0
#> 972 1 63.46 C 30 3.0
#> 973 1 63.46 C 20 3.0
#> 974 1 33.22 C 30 3.0
#> 975 0 63.46 C 30 3.0
#> 976 0 63.46 C 30 3.0
#> 977 0 63.46 C 30 3.0
#> 978 0 63.46 C 30 3.0
#> 979 1 63.46 R 30 3.2
#> 980 1 33.22 C 30 3.0
#> 981 1 63.46 R 30 3.2
#> 982 0 63.46 C 30 -9.0
#> 983 0 63.46 C 30 -9.0
#> 984 1 63.46 C 30 3.0
#> 985 1 63.46 C 30 3.0
#> 986 0 39.80 C 30 -9.0
#> 987 1 63.46 R 31 3.1
#> 988 1 63.46 R 30 3.1
#> 989 1 63.46 R 31 3.2
#> 990 1 -9.00 C 45 3.5
#> 991 1 63.46 C 30 -9.0
#> 992 1 63.46 C 15 -9.0
#> 993 1 63.46 C 30 3.0
#> 994 1 63.46 C 30 3.0
#> 995 0 63.46 C 30 -9.0
#> 996 1 63.46 R 31 2.9
#> 997 1 36.00 C 30 3.4
#> 998 1 36.00 C 30 3.8
#> 999 1 28.00 C 60 -9.0
#> 1000 1 160.00 C 30 3.3
#> 1001 1 28.00 C 30 -9.0
#> 1002 1 63.46 C 30 2.9
#> 1003 1 63.46 R 30 3.1
#> 1004 1 63.46 R 31 3.0
#> 1005 1 63.46 R 30 3.0
#> 1006 1 63.46 R 30 3.0
#> 1007 1 63.46 C 30 3.1
#> 1008 1 63.46 C 30 3.0
#> 1009 1 -9.00 C 61 -9.0
#> 1010 1 -9.00 C 63 -9.0
#> 1011 1 35.20 C 60 -9.0
#> 1012 1 -9.00 C 62 -9.0
#> 1013 1 35.20 C 60 3.5
#> 1014 1 35.20 C 60 3.4
#> 1015 1 -9.00 C 60 -9.0
#> 1016 1 -9.00 C 60 -9.0
#> 1017 1 -9.00 C 60 -9.0
#> 1018 1 -9.00 C 60 -9.0
#> 1019 1 35.20 C 60 3.5
#> 1020 1 35.20 C 60 3.5
#> 1021 1 35.20 C 60 3.5
#> 1022 1 35.20 C 60 3.5
#> 1023 1 63.46 R 30 3.0
#> 1024 1 33.22 R 30 3.5
#> 1025 1 63.46 R 30 3.0
#> 1026 1 63.46 C 30 3.0
#> 1027 1 63.46 C 30 3.0
#> 1028 0 63.46 C 30 3.0
#> 1029 0 63.46 C 30 3.0
#> 1030 1 63.46 R 31 3.0
#> 1031 1 63.46 R 30 3.3
#> 1032 1 63.46 R 31 3.2
#> 1033 1 160.00 C 30 3.5
#> 1034 1 63.46 R 30 3.2
#> 1035 1 160.00 C 30 3.7
#> 1036 1 63.46 R 30 3.0
#> 1037 1 63.46 R 30 3.3
#> 1038 1 63.46 C 30 3.0
#> 1039 1 36.00 C 30 4.0
#> 1040 1 -9.00 R 60 -9.0
#> 1041 1 -9.00 R 60 -9.0
#> 1042 1 -9.00 C 60 -9.0
#> 1043 1 -9.00 C 25 -9.0
#> 1044 1 -9.00 C 60 -9.0
#> 1045 1 -9.00 C 50 -9.0
#> 1046 1 -9.00 R 60 -9.0
#> 1047 1 -9.00 R 60 -9.0
#> 1048 1 83.00 C 30 3.6
#> 1049 1 -9.00 R 60 3.5
#> 1050 1 -9.00 R 60 4.6
#> 1051 1 -9.00 C 30 3.0
#> 1052 1 83.00 C 30 3.8
#> 1053 1 -9.00 C 30 3.0
#> 1054 1 83.00 C 30 3.6
#> 1055 1 83.00 C 30 3.8
#> 1056 1 83.00 C 30 3.6
#> 1057 1 63.46 R 30 3.0
#> 1058 1 63.46 R 30 3.0
#> 1059 1 63.46 C 15 3.0
#> 1060 1 63.46 R 30 3.1
#> 1061 1 63.46 R 29 3.3
#> 1062 1 63.46 R 30 3.2
#> 1063 1 33.22 R 30 3.4
#> 1064 0 63.46 C 30 3.0
#> 1065 1 63.46 C 30 2.9
#> 1066 1 63.46 C 30 3.2
#> 1067 1 -9.00 R 60 3.3
#> 1068 1 83.00 C 30 3.7
#> 1069 1 83.00 C 30 3.5
#> 1070 1 83.00 C 30 3.5
#> 1071 1 83.00 C 30 3.7
#> 1072 1 83.00 C 30 3.5
#> 1073 1 28.00 C 60 -9.0
#> 1074 1 36.00 C 30 3.6
#> 1075 1 33.22 C 30 3.0
#> 1076 0 63.46 C 30 -9.0
#> 1077 1 63.46 R 30 3.2
#> 1078 1 63.46 R 30 3.4
#> 1079 1 63.46 R 30 3.1
#> 1080 0 63.46 C 30 -9.0
#> 1081 1 63.46 R 30 3.2
#> 1082 1 63.46 R 30 3.6
#> 1083 1 36.00 C 30 3.4
#> 1084 1 36.00 C 30 3.6
#> 1085 1 83.00 C 60 3.3
#> 1086 1 83.00 C 30 3.0
#> 1087 1 63.46 R 30 2.9
#> 1088 1 63.46 R 30 2.9
#> 1089 1 63.46 R 30 3.1
#> 1090 1 63.46 R 30 2.8
#> 1091 1 -9.00 R 60 3.1
#> 1092 0 39.80 C 30 -9.0
#> 1093 0 39.80 C 30 -9.0
#> 1094 0 39.80 C 30 -9.0
#> 1095 1 83.00 C 30 3.3
#> 1096 1 83.00 C 30 3.5
#> 1097 1 -9.00 C 30 3.6
#> 1098 1 63.46 R 30 3.0
#> 1099 1 63.46 C 30 3.0
#> 1100 1 63.46 C 30 3.1
#> 1101 1 63.46 C 30 3.1
#> 1102 1 63.46 C 20 3.0
#> 1103 1 63.46 C 30 2.9
#> 1104 1 -9.00 R 59 3.9
#> 1105 1 36.00 C 30 3.6
#> 1106 1 28.00 C 60 -9.0
#> 1107 1 83.00 C 30 3.5
#> 1108 1 63.46 R 30 2.9
#> 1109 1 63.46 C 30 2.9
#> 1110 1 63.46 C 30 3.1
#> 1111 1 63.46 R 30 2.9
#> 1112 1 63.46 C 30 3.0
#> 1113 1 63.46 R 30 2.9
#> 1114 1 63.46 C 30 3.0
#> 1115 0 63.46 C 30 3.0
#> 1116 1 35.20 C 60 3.5
#> 1117 1 35.20 C 60 -9.0
#> 1118 1 35.20 C 60 3.4
#> 1119 1 83.00 C 60 3.2
#> 1120 1 83.00 C 30 3.4
#> 1121 1 83.00 C 30 3.2
#> 1122 1 -9.00 C 60 -9.0
#> 1123 1 -9.00 C 60 -9.0
#> 1124 1 -9.00 C 60 -9.0
#> 1125 1 -9.00 C 60 -9.0
#> 1126 1 -9.00 C 60 -9.0
#> 1127 1 -9.00 C 60 -9.0
#> 1128 1 28.00 C 30 -9.0
#> 1129 1 35.20 C 60 3.5
#> 1130 1 28.00 C 30 -9.0
#> 1131 1 28.00 C 60 -9.0
#> 1132 0 39.80 C 30 -9.0
#> 1133 1 28.00 C 60 -9.0
#> 1134 0 39.80 C 30 -9.0
#> 1135 1 -9.00 R 60 2.9
#> 1136 1 -9.00 R 60 2.9
#> 1137 0 39.80 C 30 -9.0
#> 1138 1 160.00 C 30 3.6
#> 1139 1 63.46 R 30 2.9
#> 1140 1 63.46 R 30 3.1
#> 1141 1 63.46 C 30 3.0
#> 1142 1 -9.00 R 60 -9.0
#> 1143 1 -9.00 C 70 -9.0
#> 1144 1 -9.00 C 120 3.3
#> 1145 1 160.00 C 30 3.6
#> 1146 1 160.00 C 30 3.7
#> 1147 1 -9.00 R 60 4.9
#> 1148 1 36.00 C 30 3.4
#> 1149 1 36.00 C 30 3.6
#> 1150 1 -9.00 R 60 3.0
#> 1151 1 -9.00 C 30 3.0
#> 1152 1 -9.00 C 30 3.0
#> 1153 0 39.80 C 30 -9.0
#> 1154 1 83.00 C 30 3.5
#> 1155 1 33.22 R 30 3.4
#> 1156 1 33.22 R 30 3.1
#> 1157 1 63.46 R 31 3.1
#> 1158 1 63.46 C 30 3.2
#> 1159 1 33.22 R 29 3.3
#> 1160 1 63.46 C 30 3.0
#> 1161 1 63.46 C 30 3.2
#> 1162 1 63.46 R 30 3.0
#> 1163 1 63.46 R 30 1.7
#> 1164 1 63.46 C 30 3.0
#> 1165 1 63.46 R 30 3.2
#> 1166 1 63.46 C 30 3.0
#> 1167 1 63.46 R 29 3.0
#> 1168 0 63.46 C 30 -9.0
#> 1169 1 63.46 R 30 3.2
#> 1170 0 39.80 C 30 -9.0
#> 1171 1 28.00 C 60 -9.0
#> 1172 1 83.00 C 30 3.5
#> 1173 1 83.00 C 34 3.3
#> 1174 1 -9.00 C 60 -9.0
#> 1175 1 -9.00 C 60 -9.0
#> 1176 1 -9.00 C 60 -9.0
#> 1177 1 36.00 C 30 3.4
#> 1178 1 36.00 C 30 3.6
#> 1179 1 36.00 C 30 3.6
#> 1180 1 160.00 C 60 2.9
#> 1181 1 83.00 C 60 3.4
#> 1182 1 83.00 C 60 3.3
#> 1183 1 83.00 C 52 2.8
#> 1184 1 63.46 R 30 3.1
#> 1185 1 63.46 C 30 3.1
#> 1186 1 63.46 C 30 3.1
#> 1187 1 63.46 R 30 3.1
#> 1188 1 63.46 R 33 3.1
#> 1189 1 63.46 R 31 3.0
#> 1190 1 33.22 R 30 3.0
#> 1191 1 63.46 C 30 3.0
#> 1192 1 63.46 C 30 3.2
#> 1193 1 63.46 R 31 2.9
#> 1194 1 63.46 R 30 3.0
#> 1195 1 63.46 C 30 3.2
#> 1196 1 -9.00 R 60 3.3
#> 1197 1 -9.00 R 60 3.2
#> 1198 1 -9.00 R 59 3.4
#> 1199 0 39.80 C 30 -9.0
#> 1200 0 39.80 C 30 -9.0
#> 1201 0 39.80 C 30 -9.0
#> 1202 0 39.80 C 30 -9.0
#> 1203 1 -9.00 C 30 3.7
#> 1204 1 -9.00 C 30 3.7
#> 1205 1 83.00 C 22 3.5
#> 1206 1 63.46 C 30 3.0
#> 1207 1 63.46 C 30 2.9
#> 1208 1 33.22 R 30 3.2
#> 1209 1 63.46 R 30 3.0
#> 1210 1 63.46 R 30 3.1
#> 1211 1 63.46 C 30 3.0
#> 1212 1 63.46 R 30 2.9
#> 1213 1 63.46 C 30 3.2
#> 1214 0 63.46 C 30 -9.0
#> 1215 1 -9.00 R 60 3.5
#> 1216 1 83.00 C 30 3.5
#> 1217 1 33.22 C 30 3.2
#> 1218 1 63.46 C 30 3.1
#> 1219 1 63.46 R 30 3.0
#> 1220 1 63.46 C 30 3.1
#> 1221 1 63.46 R 30 3.0
#> 1222 1 63.46 R 31 3.0
#> 1223 1 33.22 R 30 3.3
#> 1224 1 63.46 C 30 3.0
#> 1225 1 63.46 C 30 3.0
#> 1226 1 63.46 C 30 3.0
#> 1227 1 63.46 C 30 3.0
#> 1228 1 -9.00 C 60 -9.0
#> 1229 1 83.00 C 30 3.0
#> 1230 0 39.80 C 30 -9.0
#> 1231 1 83.00 C 30 3.2
#> 1232 1 36.00 C 30 3.6
#> 1233 1 83.00 C 30 3.2
#> 1234 1 -9.00 C 62 -9.0
#> 1235 1 -9.00 C 63 -9.0
#> 1236 1 -9.00 C 60 -9.0
#> 1237 1 -9.00 C 59 -9.0
#> 1238 1 160.00 C 60 3.2
#> 1239 1 -9.00 C 60 -9.0
#> 1240 1 -9.00 C 60 -9.0
#> 1241 1 -9.00 C 60 -9.0
#> 1242 1 -9.00 C 60 -9.0
#> 1243 1 -9.00 C 60 -9.0
#> 1244 1 35.20 C 60 3.5
#> 1245 1 35.20 C 60 3.5
#> 1246 1 35.20 C 60 3.5
#> 1247 1 35.20 C 60 3.5
#> 1248 0 39.80 C 30 -9.0
#> 1249 0 39.80 C 30 -9.0
#> 1250 1 28.00 C 30 -9.0
#> 1251 1 63.46 R 30 3.0
#> 1252 1 63.46 C 30 3.2
#> 1253 1 63.46 C 30 3.9
#> 1254 1 63.46 R 30 3.2
#> 1255 1 63.46 C 30 -9.0
#> 1256 1 -9.00 R 62 2.9
#> 1257 1 160.00 C 30 3.5
#> 1258 1 160.00 C 30 3.7
#> 1259 1 33.22 R 30 3.1
#> 1260 1 33.22 R 30 3.2
#> 1261 1 33.22 R 30 3.2
#> 1262 1 63.46 R 30 2.9
#> 1263 1 63.46 C 30 3.0
#> 1264 1 63.46 C 30 -9.0
#> 1265 1 63.46 R 30 3.2
#> 1266 0 63.46 C 30 3.0
#> 1267 0 63.46 C 30 3.0
#> 1268 1 36.00 C 30 3.8
#> 1269 1 -9.00 C 30 3.3
#> 1270 0 39.80 C 60 -9.0
#> 1271 1 160.00 C 30 3.4
#> 1272 1 83.00 C 30 3.6
#> 1273 1 83.00 C 30 3.6
#> 1274 1 63.46 R 30 2.9
#> 1275 1 63.46 R 30 3.1
#> 1276 1 63.46 R 30 3.0
#> 1277 1 63.46 R 31 2.1
#> 1278 1 63.46 C 30 3.0
#> 1279 1 63.46 C 30 3.0
#> 1280 1 63.46 R 31 3.3
#> 1281 1 63.46 R 31 3.2
#> 1282 1 63.46 C 30 2.9
#> 1283 1 -9.00 R 60 4.3
#> 1284 1 -9.00 R 60 3.6
#> 1285 1 36.00 C 32 4.0
#> 1286 1 36.00 C 30 3.0
#> 1287 1 -9.00 R 60 4.3
#> 1288 1 -9.00 C 30 3.0
#> 1289 1 -9.00 C 30 3.0
#> 1290 1 -9.00 C 20 -9.0
#> 1291 1 83.00 C 30 3.5
#> 1292 1 83.00 C 30 3.7
#> 1293 1 83.00 C 30 3.8
#> 1294 1 83.00 C 30 3.6
#> 1295 1 160.00 C 30 3.4
#> 1296 1 63.46 R 30 2.9
#> 1297 0 63.46 C 30 -9.0
#> 1298 0 63.46 C 30 -9.0
#> 1299 1 63.46 R 31 3.3
#> 1300 1 63.46 R 30 3.1
#> 1301 1 63.46 R 30 3.2
#> 1302 1 63.46 C 30 3.0
#> 1303 1 63.46 C 30 3.0
#> 1304 0 63.46 C 30 -9.0
#> 1305 0 63.46 C 30 -9.0
#> 1306 0 63.46 C 30 -9.0
#> 1307 0 39.80 C 30 -9.0
#> 1308 1 -9.00 R 60 3.3
#> 1309 1 83.00 C 30 4.0
#> 1310 1 83.00 C 30 3.7
#> 1311 1 83.00 C 30 3.2
#> 1312 1 28.00 C 60 -9.0
#> 1313 1 83.00 C 30 3.3
#> 1314 1 28.00 C 60 -9.0
#> 1315 1 63.46 R 30 2.9
#> 1316 1 63.46 R 30 2.9
#> 1317 1 63.46 C 30 3.3
#> 1318 1 63.46 R 29 3.0
#> 1319 1 -9.00 C 60 -9.0
#> 1320 1 36.00 C 30 3.4
#> 1321 1 36.00 C 30 4.0
#> 1322 1 -9.00 C 59 -9.0
#> 1323 1 160.00 C 60 3.1
#> 1324 1 63.46 C 30 3.0
#> 1325 1 -9.00 R 60 3.2
#> 1326 1 -9.00 R 59 3.4
#> 1327 1 -9.00 R 60 3.0
#> 1328 0 39.80 C 30 -9.0
#> 1329 0 39.80 C 30 -9.0
#> 1330 0 39.80 C 30 -9.0
#> 1331 1 83.00 C 30 3.3
#> 1332 1 83.00 C 30 3.4
#> 1333 1 83.00 C 30 3.2
#> 1334 1 -9.00 C 30 3.6
#> 1335 0 63.46 C 30 -9.0
#> 1336 1 63.46 C 20 3.0
#> 1337 1 63.46 R 30 2.9
#> 1338 1 63.46 R 30 3.0
#> 1339 1 63.46 R 30 3.3
#> 1340 1 63.46 R 30 3.0
#> 1341 1 33.22 R 30 3.5
#> 1342 0 63.46 C 30 3.1
#> 1343 1 33.22 R 30 3.4
#> 1344 1 63.46 R 30 3.0
#> 1345 1 33.22 R 30 3.3
#> 1346 1 63.46 R 30 3.0
#> 1347 0 63.46 C 30 -9.0
#> 1348 1 63.46 C 30 2.9
#> 1349 1 -9.00 R 60 3.8
#> 1350 1 -9.00 R 60 3.2
#> 1351 1 83.00 C 30 3.8
#> 1352 0 39.80 C 30 -9.0
#> 1353 1 28.00 C 60 -9.0
#> 1354 1 83.00 C 30 3.5
#> 1355 1 83.00 C 30 3.3
#> 1356 1 83.00 C 30 3.3
#> 1357 1 36.00 C 29 3.6
#> 1358 1 -9.00 C 60 -9.0
#> 1359 1 -9.00 C 60 -9.0
#> 1360 1 83.00 C 30 3.1
#> 1361 1 83.00 C 30 2.8
#> 1362 1 83.00 C 30 3.4
#> 1363 1 -9.00 C 61 -9.0
#> 1364 1 35.20 C 60 3.4
#> 1365 1 35.20 C 60 3.5
#> 1366 1 -9.00 C 61 -9.0
#> 1367 1 -9.00 C 63 -9.0
#> 1368 1 -9.00 C 60 -9.0
#> 1369 1 -9.00 C 60 -9.0
#> 1370 1 -9.00 C 60 -9.0
#> 1371 1 -9.00 C 60 -9.0
#> 1372 1 -9.00 C 60 -9.0
#> 1373 1 -9.00 C 60 -9.0
#> 1374 1 35.20 C 60 3.5
#> 1375 1 35.20 C 60 3.5
#> 1376 1 35.20 C 60 3.5
#> 1377 1 35.20 C 60 3.6
#> 1378 1 28.00 C 30 -9.0
#> 1379 0 39.80 C 30 -9.0
#> 1380 1 63.46 R 30 3.1
#> 1381 1 63.46 R 31 3.0
#> 1382 1 63.46 C 30 -9.0
#> 1383 1 160.00 C 30 3.5
#> 1384 1 160.00 C 30 3.4
#> 1385 1 63.46 R 30 2.9
#> 1386 1 63.46 R 30 3.0
#> 1387 1 63.46 R 30 2.9
#> 1388 1 33.22 C 30 3.0
#> 1389 1 63.46 R 30 3.2
#> 1390 0 63.46 C 30 3.0
#> 1391 0 63.46 C 30 3.0
#> 1392 0 63.46 C 30 3.0
#> 1393 1 63.46 C 30 3.0
#> 1394 1 63.46 R 30 3.0
#> 1395 1 63.46 R 30 0.1
#> 1396 1 63.46 R 30 3.0
#> 1397 1 33.22 R 30 3.3
#> 1398 1 63.46 C 30 3.0
#> 1399 1 63.46 C 30 3.0
#> 1400 1 63.46 C 20 3.0
#> 1401 1 63.46 R 30 3.1
#> 1402 1 63.46 C 30 3.0
#> 1403 1 63.46 C 30 3.0
#> 1404 1 63.46 R 30 2.9
#> 1405 0 63.46 C 30 -9.0
#> 1406 0 63.46 C 30 -9.0
#> 1407 1 63.46 R 29 3.0
#> 1408 1 63.46 C 30 3.0
#> 1409 0 63.46 C 30 -9.0
#> 1410 1 33.22 R 30 3.3
#> 1411 0 63.46 C 30 -9.0
#> 1412 1 33.22 R 30 3.0
#> 1413 1 -9.00 R 60 -9.0
#> 1414 1 -9.00 C 25 -9.0
#> 1415 1 160.00 C 30 3.5
#> 1416 1 -9.00 C 30 3.2
#> 1417 1 -9.00 C 25 3.3
#> 1418 1 83.00 C 30 3.7
#> 1419 1 83.00 C 30 3.4
#> 1420 1 36.00 C 30 -9.0
#> 1421 1 83.00 C 30 3.9
#> 1422 1 83.00 C 30 3.7
#> 1423 1 83.00 C 30 3.8
#> 1424 1 83.00 C 30 3.6
#> 1425 1 36.00 C 30 3.6
#> 1426 1 36.00 C 14 2.4
#> 1427 1 36.00 C 30 3.0
#> 1428 1 -9.00 C 30 3.0
#> 1429 1 83.00 C 30 3.5
#> 1430 1 83.00 C 30 3.8
#> 1431 1 83.00 C 30 3.7
#> 1432 1 83.00 C 30 3.5
#> 1433 1 160.00 C 30 3.4
#> 1434 1 83.00 C 25 3.5
#> 1435 1 33.22 R 30 3.0
#> 1436 0 39.80 C 30 -9.0
#> 1437 0 39.80 C 30 -9.0
#> 1438 0 39.80 C 30 -9.0
#> 1439 1 83.00 C 30 3.5
#> 1440 1 83.00 C 30 3.5
#> 1441 1 33.22 C 30 3.2
#> 1442 1 63.46 C 28 3.0
#> 1443 1 63.46 C 20 3.1
#> 1444 1 63.46 C 30 3.2
#> 1445 1 63.46 C 30 3.0
#> 1446 1 63.46 C 30 3.1
#> 1447 1 63.46 C 30 3.0
#> 1448 1 -9.00 C 60 -9.0
#> 1449 1 63.46 R 30 2.5
#> 1450 1 63.46 C 30 3.1
#> 1451 1 63.46 R 30 3.0
#> 1452 1 33.22 R 31 3.4
#> 1453 1 63.46 C 30 3.0
#> 1454 1 63.46 C 30 3.0
#> 1455 1 63.46 C 30 3.0
#> 1456 0 63.46 C 30 -9.0
#> 1457 1 36.00 C 30 3.4
#> 1458 1 -9.00 R 59 3.4
#> 1459 1 -9.00 R 60 3.1
#> 1460 0 39.80 C 30 -9.0
#> 1461 1 83.00 C 30 3.6
#> 1462 1 -9.00 C 60 3.9
#> 1463 1 83.00 C 30 3.6
#> 1464 1 36.00 C 30 3.4
#> 1465 1 33.22 R 22 2.7
#> 1466 1 63.46 R 30 3.0
#> 1467 0 63.46 C 30 3.2
#> 1468 1 63.46 R 30 3.0
#> 1469 1 63.46 R 31 3.0
#> 1470 1 63.46 R 30 3.3
#> 1471 1 63.46 R 29 3.0
#> 1472 1 63.46 R 30 3.0
#> 1473 1 63.46 R 31 3.0
#> 1474 1 63.46 C 30 3.1
#> 1475 0 63.46 C 30 -9.0
#> 1476 1 -9.00 R 60 3.5
#> 1477 1 -9.00 R 59 3.4
#> 1478 1 -9.00 C 60 -9.0
#> 1479 1 83.00 C 30 3.2
#> 1480 1 -9.00 C 60 -9.0
#> 1481 1 160.00 C 30 3.0
#> 1482 1 83.00 C 30 3.2
#> 1483 1 35.20 C 60 3.4
#> 1484 1 -9.00 C 60 -9.0
#> 1485 1 35.20 C 60 3.4
#> 1486 1 35.20 C 60 3.4
#> 1487 1 35.20 C 60 3.5
#> 1488 1 160.00 C 60 2.7
#> 1489 1 83.00 C 60 3.2
#> 1490 1 160.00 C 60 3.1
#> 1491 1 160.00 C 60 3.2
#> 1492 1 160.00 C 60 3.2
#> 1493 1 63.46 R 31 3.1
#> 1494 1 33.22 R 30 3.1
#> 1495 1 63.46 C 30 3.0
#> 1496 1 63.46 C 30 3.0
#> 1497 1 63.46 R 30 3.0
#> 1498 1 63.46 R 30 3.0
#> 1499 1 33.22 R 30 3.3
#> 1500 1 33.22 R 30 3.2
#> 1501 1 63.46 R 30 2.2
#> 1502 0 63.46 C 30 -9.0
#> 1503 1 63.46 C 30 3.1
#> 1504 0 63.46 C 30 3.0
#> 1505 0 63.46 C 30 3.0
#> 1506 0 63.46 C 30 3.0
#> 1507 1 -9.00 C 60 -9.0
#> 1508 1 -9.00 C 60 -9.0
#> 1509 1 -9.00 C 60 -9.0
#> 1510 1 -9.00 C 60 -9.0
#> 1511 1 -9.00 C 60 -9.0
#> 1512 1 35.20 C 60 3.5
#> 1513 1 35.20 C 60 3.5
#> 1514 1 28.00 C 30 -9.0
#> 1515 1 28.00 C 30 -9.0
#> 1516 0 39.80 C 30 -9.0
#> 1517 1 160.00 C 30 3.5
#> 1518 1 63.46 R 30 3.0
#> 1519 1 63.46 R 30 2.9
#> 1520 1 63.46 R 30 3.0
#> 1521 1 63.46 R 30 2.9
#> 1522 1 63.46 R 30 1.7
#> 1523 1 63.46 C 30 3.0
#> 1524 1 63.46 C 30 3.0
#> 1525 1 63.46 C 15 -9.0
#> 1526 1 63.46 R 31 3.3
#> 1527 1 63.46 R 31 3.2
#> 1528 1 63.46 R 30 3.2
#> 1529 1 63.46 R 30 3.3
#> 1530 1 63.46 R 31 3.0
#> 1531 1 63.46 C 30 3.0
#> 1532 1 33.22 R 30 3.3
#> 1533 0 63.46 C 30 -9.0
#> 1534 1 63.46 R 30 2.9
#> 1535 1 33.22 R 30 3.3
#> 1536 1 63.46 C 30 3.0
#> 1537 1 63.46 R 30 3.2
#> 1538 1 63.46 R 30 3.2
#> 1539 1 63.46 C 30 3.0
#> 1540 1 -9.00 R 60 4.0
#> 1541 1 -9.00 R 60 3.3
#> 1542 1 36.00 C 30 3.4
#> 1543 1 -9.00 R 60 3.4
#> 1544 1 -9.00 R 60 3.0
#> 1545 1 -9.00 C 30 3.0
#> 1546 1 -9.00 C 30 3.0
#> 1547 1 -9.00 C 30 3.0
#> 1548 1 83.00 C 30 3.8
#> 1549 0 39.80 C 30 -9.0
#> 1550 1 83.00 C 30 3.7
#> 1551 1 83.00 C 30 3.4
#> 1552 1 160.00 C 30 3.5
#> 1553 1 -9.00 R 59 -9.0
#> 1554 1 36.00 C 31 3.8
#> 1555 1 -9.00 R 60 -9.0
#> 1556 1 -9.00 R 60 -9.0
#> 1557 1 -9.00 C 70 -9.0
#> 1558 1 -9.00 C 50 -9.0
#> 1559 1 160.00 C 30 3.7
#> 1560 1 160.00 C 30 3.7
#> 1561 1 63.46 R 30 3.3
#> 1562 1 63.46 R 30 3.3
#> 1563 1 63.46 C 20 -9.0
#> 1564 1 -9.00 R 60 3.5
#> 1565 1 -9.00 R 60 3.8
#> 1566 0 39.80 C 30 -9.0
#> 1567 0 39.80 C 30 -9.0
#> 1568 1 83.00 C 30 3.5
#> 1569 1 83.00 C 30 3.2
#> 1570 1 83.00 C 30 3.6
#> 1571 1 83.00 C 30 3.7
#> 1572 1 28.00 C 60 -9.0
#> 1573 1 63.46 R 30 3.0
#> 1574 1 63.46 C 30 -9.0
#> 1575 1 33.22 C 30 3.2
#> 1576 1 63.46 R 30 2.7
#> 1577 0 63.46 C 30 -9.0
#> 1578 0 63.46 C 30 -9.0
#> 1579 1 63.46 C 30 3.0
#> 1580 1 63.46 C 30 3.0
#> 1581 1 63.46 R 30 3.2
#> 1582 1 63.46 R 30 3.0
#> 1583 1 33.22 C 30 -9.0
#> 1584 0 63.46 C 30 -9.0
#> 1585 1 63.46 C 30 3.0
#> 1586 1 63.46 R 30 2.9
#> 1587 1 63.46 C 30 3.1
#> 1588 1 63.46 C 30 3.1
#> 1589 0 63.46 C 30 -9.0
#> 1590 1 36.00 C 30 3.6
#> 1591 1 36.00 C 30 3.4
#> 1592 1 83.00 C 60 3.3
#> 1593 1 83.00 C 60 3.0
#> 1594 1 83.00 C 60 3.0
#> 1595 1 36.00 C 30 3.8
#> 1596 1 63.46 R 30 2.9
#> 1597 0 63.46 C 30 3.0
#> 1598 1 63.46 R 30 2.9
#> 1599 0 63.46 C 30 3.2
#> 1600 0 63.46 C 30 3.0
#> 1601 0 63.46 C 30 3.0
#> 1602 0 63.46 C 30 3.1
#> 1603 0 63.46 C 30 3.0
#> 1604 1 63.46 R 31 3.0
#> 1605 1 63.46 C 30 3.1
#> 1606 1 63.46 C 30 3.0
#> 1607 1 -9.00 R 51 3.4
#> 1608 1 -9.00 R 60 3.5
#> 1609 1 -9.00 R 60 3.0
#> 1610 0 39.80 C 30 -9.0
#> 1611 1 83.00 C 30 3.7
#> 1612 1 -9.00 C 30 3.7
#> 1613 1 83.00 C 30 3.6
#> 1614 1 83.00 C 30 3.5
#> 1615 1 83.00 C 30 3.5
#> 1616 1 83.00 C 22 3.5
#> 1617 1 63.46 R 30 3.0
#> 1618 1 63.46 C 30 3.0
#> 1619 1 63.46 C 30 3.0
#> 1620 1 63.46 R 30 3.1
#> 1621 1 63.46 R 30 3.1
#> 1622 1 63.46 C 30 3.0
#> 1623 1 63.46 C 30 3.2
#> 1624 1 63.46 C 30 3.2
#> 1625 1 63.46 R 30 3.0
#> 1626 1 -9.00 C 30 3.5
#> 1627 1 83.00 C 30 3.3
#> 1628 1 -9.00 C 60 -9.0
#> 1629 1 160.00 C 30 3.0
#> 1630 1 83.00 C 30 3.3
#> 1631 1 83.00 C 30 3.2
#> 1632 1 83.00 C 30 3.2
#> 1633 1 83.00 C 30 3.2
#> 1634 1 63.46 R 30 3.1
#> 1635 1 63.46 R 25 3.0
#> 1636 1 63.46 C 30 3.0
#> 1637 1 63.46 C 30 3.0
#> 1638 1 -9.00 C 61 -9.0
#> 1639 1 35.20 C 60 3.5
#> 1640 1 35.20 C 60 3.1
#> 1641 1 -9.00 C 61 -9.0
#> 1642 1 35.20 C 60 3.4
#> 1643 1 35.20 C 60 3.5
#> 1644 1 36.00 C 30 3.0
#> 1645 1 -9.00 C 61 -9.0
#> 1646 1 160.00 C 60 2.8
#> 1647 1 83.00 C 60 3.2
#> 1648 1 63.46 R 30 3.0
#> 1649 1 63.46 R 31 3.3
#> 1650 1 63.46 R 30 2.9
#> 1651 1 63.46 R 30 3.3
#> 1652 1 63.46 C 30 3.0
#> 1653 1 63.46 C 30 3.1
#> 1654 0 63.46 C 30 3.0
#> 1655 1 63.46 C 15 -9.0
#> 1656 1 63.46 C 30 3.0
#> 1657 1 63.46 C 30 2.9
#> 1658 0 63.46 C 30 -9.0
#> 1659 1 63.46 R 30 3.1
#> 1660 1 63.46 R 29 3.0
#> 1661 1 63.46 R 30 2.9
#> 1662 1 63.46 R 30 3.0
#> 1663 1 63.46 R 30 3.0
#> 1664 1 63.46 R 30 3.0
#> 1665 1 63.46 R 30 2.9
#> 1666 1 63.46 C 30 3.0
#> 1667 1 63.46 C 15 3.0
#> 1668 1 63.46 R 31 3.2
#> 1669 1 63.46 R 30 3.0
#> 1670 1 63.46 R 30 3.1
#> 1671 1 63.46 R 30 3.1
#> 1672 1 63.46 C 30 3.1
#> 1673 1 63.46 C 30 3.0
#> 1674 1 63.46 C 30 3.0
#> 1675 1 63.46 R 30 3.2
#> 1676 1 63.46 C 30 3.0
#> 1677 0 63.46 C 30 -9.0
#> 1678 1 36.00 C 30 3.2
#> 1679 1 -9.00 R 29 3.0
#> 1680 1 -9.00 R 60 3.0
#> 1681 1 36.00 C 30 3.4
#> 1682 1 -9.00 C 30 3.5
#> 1683 0 39.80 C 30 -9.0
#> 1684 1 160.00 C 30 3.5
#> 1685 1 160.00 C 30 3.4
#> 1686 1 -9.00 C 60 -9.0
#> 1687 1 -9.00 C 60 -9.0
#> 1688 1 -9.00 C 60 -9.0
#> 1689 1 -9.00 C 60 -9.0
#> 1690 1 -9.00 C 60 -9.0
#> 1691 1 -9.00 C 60 -9.0
#> 1692 1 35.20 C 60 3.5
#> 1693 1 28.00 C 30 -9.0
#> 1694 1 35.20 C 60 3.5
#> 1695 1 35.20 C 60 3.5
#> 1696 1 35.20 C 60 3.5
#> 1697 1 63.46 R 30 3.1
#> 1698 1 63.46 R 30 3.3
#> 1699 1 63.46 R 30 3.0
#> 1700 1 36.00 C 30 4.0
#> 1701 1 -9.00 R 59 4.2
#> 1702 1 36.00 C 30 3.8
#> 1703 1 -9.00 R 60 4.6
#> 1704 1 -9.00 R 60 4.3
#> 1705 1 -9.00 R 60 3.0
#> 1706 1 -9.00 R 60 3.5
#> 1707 1 -9.00 R 60 3.6
#> 1708 1 83.00 C 30 3.9
#> 1709 1 83.00 C 30 3.5
#> 1710 1 -9.00 R 60 -9.0
#> 1711 1 36.00 C 31 3.8
#> 1712 1 36.00 C 30 3.4
#> 1713 1 -9.00 R 60 -9.0
#> 1714 1 -9.00 C 30 3.3
#> 1715 1 160.00 C 30 3.4
#> 1716 1 -9.00 C 30 3.2
#> 1717 1 -9.00 C 30 3.2
#> 1718 1 83.00 C 30 3.7
#> 1719 1 36.00 C 30 -9.0
#> 1720 1 83.00 C 30 3.6
#> 1721 1 83.00 C 30 3.6
#> 1722 1 -9.00 R 60 3.7
#> 1723 1 -9.00 R 61 3.7
#> 1724 0 39.80 C 30 -9.0
#> 1725 0 39.80 C 30 -9.0
#> 1726 0 39.80 C 30 -9.0
#> 1727 1 -9.00 C 30 3.5
#> 1728 1 83.00 C 30 3.2
#> 1729 1 83.00 C 30 3.7
#> 1730 1 83.00 C 30 3.3
#> 1731 1 33.22 C 30 3.1
#> 1732 1 63.46 R 30 3.0
#> 1733 1 63.46 R 30 2.8
#> 1734 1 63.46 C 30 3.0
#> 1735 1 63.46 C 30 3.2
#> 1736 1 63.46 C 30 3.2
#> 1737 1 63.46 C 35 3.3
#> 1738 1 33.22 C 30 3.2
#> 1739 1 63.46 C 30 3.1
#> 1740 1 63.46 C 30 3.0
#> 1741 0 63.46 C 30 -9.0
#> 1742 1 63.46 C 30 3.1
#> 1743 1 63.46 C 30 3.1
#> 1744 0 63.46 C 30 -9.0
#> 1745 1 63.46 R 30 3.0
#> 1746 1 63.46 C 30 3.2
#> 1747 1 63.46 C 30 3.1
#> 1748 1 63.46 R 30 3.0
#> 1749 1 33.22 C 30 -9.0
#> 1750 0 63.46 C 30 -9.0
#> 1751 1 63.46 R 31 3.2
#> 1752 1 33.22 R 30 3.6
#> 1753 1 33.22 R 30 3.6
#> 1754 1 63.46 R 30 3.0
#> 1755 1 33.22 R 30 3.6
#> 1756 0 63.46 C 30 3.1
#> 1757 0 63.46 C 30 3.0
#> 1758 0 63.46 C 30 3.1
#> 1759 1 63.46 C 30 3.0
#> 1760 1 63.46 R 31 3.0
#> 1761 1 63.46 R 30 3.3
#> 1762 1 33.22 R 30 3.3
#> 1763 1 36.00 C 30 3.2
#> 1764 1 -9.00 C 60 -9.0
#> 1765 1 -9.00 C 61 -9.0
#> 1766 1 83.00 C 60 3.2
#> 1767 1 83.00 C 60 3.2
#> 1768 1 83.00 C 30 3.3
#> 1769 1 63.46 R 30 2.8
#> 1770 1 -9.00 R 60 3.2
#> 1771 1 -9.00 R 60 3.1
#> 1772 1 -9.00 C 30 3.6
#> 1773 0 39.80 C 30 -9.0
#> 1774 0 39.80 C 30 -9.0
#> 1775 0 39.80 C 30 -9.0
#> 1776 1 83.00 C 30 3.6
#> 1777 1 83.00 C 30 3.6
#> 1778 1 83.00 C 30 3.8
#> 1779 1 33.22 C 30 3.1
#> 1780 1 63.46 C 30 3.2
#> 1781 1 63.46 C 30 3.1
#> 1782 1 33.22 C 30 3.1
#> 1783 1 63.46 R 30 3.0
#> 1784 1 33.22 C 30 3.2
#> 1785 1 63.46 R 30 3.1
#> 1786 1 -9.00 R 60 3.6
#> 1787 1 -9.00 C 30 3.5
#> 1788 0 39.80 C 30 -9.0
#> 1789 1 83.00 C 30 3.3
#> 1790 1 83.00 C 30 3.3
#> 1791 1 28.00 C 30 -9.0
#> 1792 1 83.00 C 30 3.4
#> 1793 1 -9.00 C 60 -9.0
#> 1794 1 83.00 C 30 3.2
#> 1795 1 -9.00 C 60 -9.0
#> 1796 1 83.00 C 30 3.2
#> 1797 1 83.00 C 30 3.1
#> 1798 1 160.00 C 30 3.0
#> 1799 0 39.80 C 30 -9.0
#> 1800 1 83.00 C 30 3.4
#> 1801 1 83.00 C 30 3.2
#> 1802 1 83.00 C 30 3.2
#> 1803 1 63.46 R 29 3.0
#> 1804 1 63.46 R 30 3.2
#> 1805 1 33.22 R 30 3.3
#> 1806 1 63.46 C 10 3.0
#> 1807 1 63.46 R 30 2.8
#> 1808 1 63.46 R 30 2.2
#> 1809 1 63.46 C 30 3.1
#> 1810 1 33.22 R 30 3.3
#> 1811 1 63.46 R 30 3.5
#> 1812 1 63.46 C 30 3.0
#> 1813 1 63.46 C 30 3.0
#> 1814 1 63.46 C 30 3.1
#> 1815 1 63.46 C 15 -9.0
#> 1816 1 63.46 C 30 3.1
#> 1817 1 63.46 C 30 3.2
#> 1818 1 -9.00 C 64 -9.0
#> 1819 1 -9.00 C 60 -9.0
#> 1820 1 -9.00 C 60 -9.0
#> 1821 1 -9.00 C 60 -9.0
#> 1822 1 -9.00 C 61 -9.0
#> 1823 1 -9.00 C 60 -9.0
#> 1824 1 35.20 C 50 3.0
#> 1825 1 35.20 C 60 3.4
#> 1826 1 35.20 C 60 3.5
#> 1827 1 35.20 C 60 3.4
#> 1828 1 -9.00 C 61 -9.0
#> 1829 1 160.00 C 60 3.2
#> 1830 1 63.46 R 30 3.4
#> 1831 1 63.46 R 30 3.0
#> 1832 0 63.46 C 30 -9.0
#> 1833 1 63.46 R 30 3.2
#> 1834 1 63.46 R 30 3.5
#> 1835 0 63.46 C 30 -9.0
#> 1836 1 63.46 R 31 2.9
#> 1837 1 63.46 R 29 3.0
#> 1838 1 63.46 R 30 3.1
#> 1839 1 63.46 R 30 3.2
#> 1840 1 63.46 C 30 3.0
#> 1841 1 63.46 R 30 3.0
#> 1842 1 63.46 R 30 3.1
#> 1843 1 63.46 R 30 0.1
#> 1844 1 63.46 R 30 3.0
#> 1845 1 63.46 C 30 3.0
#> 1846 1 63.46 C 15 3.0
#> 1847 1 63.46 R 31 3.3
#> 1848 1 63.46 R 30 3.3
#> 1849 1 63.46 R 30 3.0
#> 1850 1 36.00 C 30 3.2
#> 1851 1 160.00 C 30 3.5
#> 1852 1 28.00 C 30 -9.0
#> 1853 1 63.46 R 30 3.3
#> 1854 1 63.46 C 30 -9.0
#> 1855 1 63.46 R 30 3.1
#> 1856 1 33.22 R 30 3.1
#> 1857 1 -9.00 C 60 -9.0
#> 1858 1 -9.00 C 60 -9.0
#> 1859 1 -9.00 C 60 -9.0
#> 1860 1 -9.00 C 60 -9.0
#> 1861 1 -9.00 C 60 -9.0
#> 1862 1 -9.00 C 60 -9.0
#> 1863 1 -9.00 C 60 -9.0
#> 1864 1 -9.00 C 60 -9.0
#> 1865 1 35.20 C 60 3.5
#> 1866 1 35.20 C 60 3.5
#> 1867 1 35.20 C 60 3.5
#> 1868 1 35.20 C 60 3.5
#> 1869 1 35.20 C 60 3.5
#> 1870 1 35.20 C 60 3.5
#> 1871 1 28.00 C 30 -9.0
#> 1872 1 35.20 C 60 3.4
#> 1873 1 35.20 C 60 3.5
#> 1874 1 35.20 C 60 3.4
#> 1875 1 35.20 C 60 3.5
#> 1876 1 28.00 C 15 -9.0
#> 1877 0 39.80 C 30 -9.0
#> 1878 1 28.00 C 60 -9.0
#> 1879 0 39.80 C 30 -9.0
#> 1880 0 39.80 C 30 -9.0
#> 1881 1 28.00 C 60 -9.0
#> 1882 1 28.00 C 60 -9.0
#> 1883 1 28.00 C 30 -9.0
#> 1884 1 -9.00 R 60 3.8
#> 1885 1 -9.00 R 60 4.9
#> 1886 1 -9.00 R 60 3.0
#> 1887 1 -9.00 R 60 4.3
#> 1888 1 -9.00 C 30 3.0
#> 1889 1 -9.00 C 30 3.0
#> 1890 1 83.00 C 30 4.0
#> 1891 1 83.00 C 30 3.7
#> 1892 1 83.00 C 30 3.6
#> 1893 1 83.00 C 30 3.9
#> 1894 1 83.00 C 30 3.5
#> 1895 1 83.00 C 30 3.7
#> 1896 1 63.46 R 29 3.1
#> 1897 1 63.46 R 30 3.0
#> 1898 1 -9.00 R 60 -9.0
#> 1899 1 36.00 C 31 3.8
#> 1900 1 -9.00 C 60 -9.0
#> 1901 1 -9.00 C 25 -9.0
#> 1902 1 -9.00 C 50 -9.0
#> 1903 1 160.00 C 30 3.4
#> 1904 1 160.00 C 30 3.5
#> 1905 1 -9.00 C 30 3.4
#> 1906 1 83.00 C 30 3.6
#> 1907 1 83.00 C 30 3.7
#> 1908 1 83.00 C 30 3.6
#> 1909 1 83.00 C 30 3.6
#> 1910 1 -9.00 R 60 2.6
#> 1911 1 36.00 C 30 3.8
#> 1912 0 39.80 C 30 -9.0
#> 1913 0 39.80 C 30 -9.0
#> 1914 0 39.80 C 30 -9.0
#> 1915 1 -9.00 C 30 3.5
#> 1916 1 -9.00 C 30 4.0
#> 1917 1 83.00 C 30 3.6
#> 1918 1 83.00 C 30 3.8
#> 1919 1 83.00 C 30 3.7
#> 1920 1 28.00 C 60 -9.0
#> 1921 1 83.00 C 30 3.5
#> 1922 1 83.00 C 34 3.3
#> 1923 1 83.00 C 30 3.5
#> haul.id ShootLat ShootLong Species CPUEun
#> 1 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 2 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 3 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 2.0000000
#> 4 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 5 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 6 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 7 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 8 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 9 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 2.0000000
#> 10 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 3.0000000
#> 11 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 1.0000000
#> 12 1996:1:DEN:DAN2:GRT:45:25 56.3700 20.0666 Gadus morhua 1.0000000
#> 13 1993:1:SWE:ARG:FOT:80:32 55.4120 15.3205 Gadus morhua 1.0000000
#> 14 1998:1:DEN:DAN2:GRT:83:40 54.8150 15.3217 Gadus morhua 2.0000000
#> 15 1994:1:DEN:DAN2:GRT:43:22 56.4500 20.2000 Gadus morhua 1.0000000
#> 16 1996:1:DEN:DAN2:GRT:9:5 54.5750 15.3200 Gadus morhua 1.0000000
#> 17 1998:1:SWE:ARG:FOT:191:3 55.8218 15.4220 Gadus morhua 2.0000000
#> 18 1993:1:GFR:SOL:H20:46:20 55.1333 14.1667 Gadus morhua 2.0000000
#> 19 2003:1:DEN:DAN2:TVL:71:36 55.3709 15.5140 Gadus morhua 2.0000000
#> 20 1991:1:LAT:90MX:LBT:000001:19 55.6167 20.0833 Gadus morhua 2.0000000
#> 21 1994:1:DEN:DAN2:GRT:117:50 54.7833 15.9500 Gadus morhua 1.0000000
#> 22 1996:1:DEN:DAN2:GRT:75:40 55.1983 16.4916 Gadus morhua 1.0000000
#> 23 2000:4:SWE:ARG:GOV:584:18 55.8150 15.3917 Gadus morhua 2.0000000
#> 24 2002:4:DEN:DAN2:TVL:10:4 55.4908 14.6121 Gadus morhua 2.0000000
#> 25 1998:1:DEN:DAN2:GRT:136:64 55.4800 18.4683 Gadus morhua 1.0000000
#> 26 1991:1:GFR:SOL:CHP:26073:50 55.2500 18.3500 Gadus morhua 1.0000000
#> 27 2002:4:SWE:ARG:TVL:573:11 56.1460 17.7615 Gadus morhua 2.0000000
#> 28 2000:1:SWE:ARG:GOV:220:21 55.0100 13.9300 Gadus morhua 2.0000000
#> 29 2000:1:SWE:ARG:GOV:237:34 55.8467 15.5717 Gadus morhua 2.0000000
#> 30 1991:1:DEN:DAN2:GRT:106:57 55.3167 17.3167 Gadus morhua 1.0000000
#> 31 1996:1:DEN:DAN2:GRT:111:47 55.2150 15.6083 Gadus morhua 1.0000000
#> 32 1996:4:SWE:ARG:FOT:231:26 57.0833 18.9000 Gadus morhua 2.0000000
#> 33 1995:4:SWE:ARG:FOT:247:2 55.8323 15.5427 Gadus morhua 2.0000000
#> 34 1999:4:SWE:ARG:GOV:652:17 55.8400 15.5600 Gadus morhua 2.0000000
#> 35 1998:1:SWE:ARG:FOT:207:15 55.9271 17.1108 Gadus morhua 2.0000000
#> 36 1993:1:DEN:DAN2:GRT:162:72 54.8500 15.6667 Gadus morhua 1.0000000
#> 37 1996:1:DEN:DAN2:GRT:53:30 56.2566 19.5666 Gadus morhua 1.0000000
#> 38 2006:1:RUS:ATLD:TVL:NA:13 55.1583 20.0267 Gadus morhua 2.0000000
#> 39 1995:1:DEN:DAN2:GRT:57:23 56.3666 19.8666 Gadus morhua 1.0000000
#> 40 2008:1:GFR:SOL2:TVS:24316:41 55.1505 14.0718 Gadus morhua 2.0000000
#> 41 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 42 1991:1:GFR:SOL:CHP:26073:50 55.2500 18.3500 Gadus morhua 1.0000000
#> 43 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 44 1998:1:SWE:ARG:FOT:222:26 57.2520 20.7436 Gadus morhua 2.0000000
#> 45 1994:1:GFR:SOL:H20:44:24 55.0333 13.4333 Gadus morhua 2.0000000
#> 46 2005:1:DEN:DAN2:TVL:95:66 55.0966 15.2680 Gadus morhua 2.0000000
#> 47 1993:1:SWE:ARG:FOT:58:10 56.0352 17.7188 Gadus morhua 1.0000000
#> 48 2001:1:DEN:DAN2:TVL:6:3 55.0214 13.7642 Gadus morhua 2.0000000
#> 49 1991:1:LAT:90MX:LBT:000001:12 55.1167 20.3333 Gadus morhua 1.0000000
#> 50 1993:1:DEN:DAN2:GRT:17:9 55.0333 14.2167 Gadus morhua 1.0000000
#> 51 1993:1:LAT:LAIZ:LBT:000001:6 55.5667 20.6500 Gadus morhua 1.0000000
#> 52 1993:4:SWE:ARG:FOT:252:21 56.1133 17.5917 Gadus morhua 3.0000000
#> 53 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 54 1998:1:RUS:ATLD:HAK:NA:35 55.5167 19.8833 Gadus morhua 3.0000000
#> 55 1998:1:RUS:ATLD:HAK:NA:33 55.6167 19.6500 Gadus morhua 2.0000000
#> 56 2009:1:DEN:DAN2:TVL:19:17 55.3195 14.9859 Gadus morhua 2.0000000
#> 57 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 58 2000:4:DEN:DAN2:TVL:94:46 55.1058 16.3850 Gadus morhua 1.9354839
#> 59 1996:1:RUS:RUEK:DT:NA:13 55.0833 18.4333 Gadus morhua 2.0000000
#> 60 1995:1:DEN:DAN2:GRT:33:14 56.4166 18.7166 Gadus morhua 1.0000000
#> 61 2010:1:DEN:DAN2:TVL:100:1 55.0897 16.3814 Gadus morhua 2.0000000
#> 62 2000:1:DEN:DAN2:GRT:16:8 55.7672 15.7198 Gadus morhua 1.0000000
#> 63 1996:1:DEN:DAN2:GRT:66:36 55.4566 17.8650 Gadus morhua 1.0000000
#> 64 1996:1:SWE:ARG:FOT:74:23 55.6700 16.4667 Gadus morhua 2.0000000
#> 65 2004:1:POL:BAL:TVL:1:1 54.5667 18.8167 Gadus morhua 2.0000000
#> 66 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 1.0000000
#> 67 1998:1:SWE:ARG:FOT:199:8 55.0090 13.9270 Gadus morhua 2.0000000
#> 68 1995:1:DEN:DAN2:GRT:123:46 55.8166 16.6666 Gadus morhua 1.0000000
#> 69 2010:1:RUS:ATL:TVL:60:17 55.3617 18.0833 Gadus morhua 2.0000000
#> 70 2009:1:SWE:ARG:TVL:267:52 55.6688 14.5024 Gadus morhua 2.0000000
#> 71 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 72 1994:4:GFR:SOL:H20:25:72 54.7167 13.1333 Gadus morhua 2.0000000
#> 73 1994:4:SWE:ARG:FOT:287:32 55.8717 16.0733 Gadus morhua 2.0000000
#> 74 2000:4:SWE:ARG:GOV:594:27 55.9362 17.0593 Gadus morhua 2.0000000
#> 75 2004:1:POL:BAL:TVL:2:2 55.2333 18.1667 Gadus morhua 2.0000000
#> 76 1998:1:RUS:ATLD:HAK:NA:37 55.5167 20.0333 Gadus morhua 2.0000000
#> 77 1995:1:DEN:DAN2:GRT:11:3 55.3166 17.2166 Gadus morhua 1.0000000
#> 78 1994:1:GFR:SOL:H20:73:34 55.6167 14.8667 Gadus morhua 2.0000000
#> 79 1996:1:DEN:DAN2:GRT:51:29 56.3450 19.6316 Gadus morhua 1.0000000
#> 80 1996:1:SWE:ARG:FOT:95:44 57.4800 17.5533 Gadus morhua 2.0000000
#> 81 2011:1:POL:BAL:TVL:26211:3 54.5267 19.3583 Gadus morhua 2.0000000
#> 82 1997:1:DEN:DAN2:GRT:18:7 55.6783 16.7883 Gadus morhua 1.0000000
#> 83 1997:4:SWE:ARG:FOT:756:26 56.2205 18.4318 Gadus morhua 2.0000000
#> 84 1991:1:LAT:90MX:LBT:000001:11 56.1167 20.5167 Gadus morhua 2.0000000
#> 85 2010:1:RUS:ATL:TVL:60:23 54.9217 19.5692 Gadus morhua 16.0000000
#> 86 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 87 1995:1:RUS:RUEK:DT:NA:19 54.9833 19.6500 Gadus morhua 2.0000000
#> 88 1994:1:DEN:DAN2:GRT:63:32 55.4667 18.5333 Gadus morhua 1.0000000
#> 89 1994:1:POL:BAL:P20:Mar:18 54.9000 18.6167 Gadus morhua 2.0000000
#> 90 1996:1:DEN:DAN2:GRT:46:26 56.4433 19.9866 Gadus morhua 1.0000000
#> 91 1999:1:RUS:ATL:HAK:NA:5 54.9500 19.6333 Gadus morhua 2.0000000
#> 92 1993:1:GFR:SOL:H20:48:22 55.0667 14.2833 Gadus morhua 2.0000000
#> 93 2001:1:GFR:SOL:TVS:902:34 55.0833 14.1500 Gadus morhua 2.0000000
#> 94 2009:4:DEN:DAN2:TVL:179:16 54.9337 16.2348 Gadus morhua 2.0000000
#> 95 2006:4:DEN:DAN2:TVL:7:32 54.9951 15.3587 Gadus morhua 1.9354839
#> 96 2003:4:RUS:ATLD:TVL:NA:60 55.2083 20.1500 Gadus morhua 2.0000000
#> 97 1992:1:DEN:DAN2:GRT:79:55 55.4667 18.2167 Gadus morhua 1.0000000
#> 98 2011:1:RUS:ATLD:TVL:56:40 55.3583 19.9267 Gadus morhua 2.0000000
#> 99 2011:4:DEN:DAN2:TVL:39:42 55.7076 14.7245 Gadus morhua 2.0689655
#> 100 1996:1:GFR:SOL:H20:47:51 55.1333 14.2667 Gadus morhua 4.0000000
#> 101 1996:4:SWE:ARG:FOT:227:22 55.8033 19.0100 Gadus morhua 2.0000000
#> 102 1996:4:GFR:SOL:H20:25:68 54.7167 13.1167 Gadus morhua 2.0000000
#> 103 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 104 1991:1:GFR:SOL:CHP:26073:50 55.2500 18.3500 Gadus morhua 1.0000000
#> 105 1999:1:POL:BAL:P20:02Feb:10 54.8670 18.9000 Gadus morhua 2.0000000
#> 106 1999:4:LAT:AA36:LBT:2:9 56.3667 20.1833 Gadus morhua 2.0000000
#> 107 1998:1:SWE:ARG:FOT:206:14 55.8513 17.6927 Gadus morhua 2.0000000
#> 108 1995:1:SWE:ARG:GOV:75:23 56.0783 17.7750 Gadus morhua 2.0000000
#> 109 2006:1:SWE:ARG:TVL:223:30 55.6878 14.8757 Gadus morhua 2.0000000
#> 110 2001:1:RUS:ATL:TVL:NA:10 55.0167 19.6833 Gadus morhua 2.0000000
#> 111 2008:4:POL:BAL:TVL:26014:21 54.4317 19.0917 Gadus morhua 2.0000000
#> 112 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 113 2008:4:RUS:ATLD:TVL:51:26 54.8267 19.6633 Gadus morhua 2.0000000
#> 114 1994:1:DEN:DAN2:GRT:118:51 54.8167 16.0500 Gadus morhua 1.0000000
#> 115 1992:1:GFR:SOL:CHP:2810:36 56.6000 20.5833 Gadus morhua 1.0000000
#> 116 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 117 2000:4:SWE:ARG:GOV:584:18 55.8150 15.3917 Gadus morhua 2.0000000
#> 118 1996:1:DEN:DAN2:GRT:36:20 57.5150 19.3750 Gadus morhua 1.0000000
#> 119 1998:1:GFR:SOL:H20:66:69 56.1000 17.6333 Gadus morhua 2.0000000
#> 120 1998:1:SWE:ARG:FOT:249:45 55.8697 16.0267 Gadus morhua 2.0000000
#> 121 1999:4:DEN:DAN2:TVL:100019:12 55.4000 17.4500 Gadus morhua 4.0000000
#> 122 1991:1:POL:AA36:P20:03Mar:2 54.6500 19.2000 Gadus morhua 2.0000000
#> 123 2009:1:DEN:DAN2:TVL:179:15 54.8195 15.9679 Gadus morhua 2.0000000
#> 124 2006:4:POL:BAL:TVL:25027:7 55.0183 17.4336 Gadus morhua 2.0000000
#> 125 1994:1:DEN:DAN2:GRT:52:26 56.1333 19.8500 Gadus morhua 1.0000000
#> 126 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 127 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 128 2000:1:RUS:ATL:HAK:NA:12 55.1667 20.0167 Gadus morhua 4.0000000
#> 129 2000:4:DEN:DAN2:GRT:75:38 55.7750 15.7781 Gadus morhua 2.0000000
#> 130 2004:1:GFR:SOL:TVS:902:34 55.0917 14.1555 Gadus morhua 2.0000000
#> 131 1996:1:DEN:DAN2:GRT:30:16 56.3000 18.5516 Gadus morhua 1.0000000
#> 132 2010:1:DEN:DAN2:TVL:98:48 55.0102 16.2765 Gadus morhua 2.0000000
#> 133 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 134 1999:1:GFR:SOL:H20:65:119 54.4833 15.7833 Gadus morhua 2.0000000
#> 135 1999:1:POL:BAL:P20:03Mar:54 55.3830 17.5000 Gadus morhua 2.0000000
#> 136 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 137 1991:1:GFR:SOL:CHP:25225:78 54.8833 15.7667 Gadus morhua 1.0000000
#> 138 2001:1:DEN:DAN2:TVL:56:27 55.4012 16.7389 Gadus morhua 4.0000000
#> 139 1993:1:POL:AA36:P20:02Feb:28 54.7167 19.2000 Gadus morhua 2.0000000
#> 140 1995:1:DEN:DAN2:GRT:134:49 55.4833 16.1500 Gadus morhua 1.0000000
#> 141 1995:4:SWE:ARG:FOT:254:9 57.0598 18.8707 Gadus morhua 2.0000000
#> 142 2003:1:DEN:DAN2:TVL:77:39 55.4620 15.0234 Gadus morhua 2.0000000
#> 143 2004:4:POL:BAL:TVL:NA:6 55.0000 18.4500 Gadus morhua 2.0000000
#> 144 2000:1:RUS:ATL:HAK:NA:18 55.3000 19.9833 Gadus morhua 3.0000000
#> 145 2000:1:SWE:ARG:FOT:270:47 56.9250 17.1733 Gadus morhua 2.0000000
#> 146 2000:4:DEN:DAN2:TVL:89:45 56.3809 20.2153 Gadus morhua 2.0000000
#> 147 1992:1:GFR:SOL:CHP:2504:46 55.3167 15.3167 Gadus morhua 1.0000000
#> 148 2010:4:DEN:DAN2:TVL:166:16 54.6558 15.0806 Gadus morhua 2.0000000
#> 149 1996:1:DEN:DAN2:GRT:62:34 55.6066 19.4466 Gadus morhua 1.0000000
#> 150 1996:1:RUS:RUEK:DT:NA:7 54.9833 19.6333 Gadus morhua 2.0000000
#> 151 1997:1:DEN:DAN2:GRT:11:4 55.1550 16.4450 Gadus morhua 1.0000000
#> 152 1997:4:SWE:ARG:FOT:746:17 56.1283 17.5800 Gadus morhua 2.0000000
#> 153 1997:4:SWE:ARG:FOT:745:16 56.0683 17.7583 Gadus morhua 1.7600000
#> 154 1998:1:RUS:ATLD:HAK:NA:34 55.6167 19.7333 Gadus morhua 2.0000000
#> 155 1998:1:POL:BAL:P20:03Mar:63 55.3167 17.3833 Gadus morhua 2.0000000
#> 156 1998:1:RUS:ATLD:HAK:NA:37 55.5167 20.0333 Gadus morhua 2.0000000
#> 157 1998:4:SWE:ARG:FOT:738:35 56.9967 17.9510 Gadus morhua 2.0000000
#> 158 1998:4:SWE:ARG:FOT:715:17 55.8560 15.5707 Gadus morhua 2.0000000
#> 159 2009:1:DEN:DAN2:TVL:266:37 55.0795 16.4275 Gadus morhua 2.0000000
#> 160 1999:1:GFR:SOL:H20:44:69 55.0333 13.4000 Gadus morhua 2.0000000
#> 161 1999:1:POL:BAL:P20:03Mar:69 54.4500 19.3333 Gadus morhua 2.0000000
#> 162 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 1.0000000
#> 163 1991:1:POL:AA36:P20:01Jan:24 54.5500 19.3667 Gadus morhua 2.0000000
#> 164 1995:1:RUS:RUEK:DT:NA:44 55.5500 20.6833 Gadus morhua 1.0000000
#> 165 1995:1:SWE:ARG:GOV:94:42 57.4767 17.0667 Gadus morhua 2.0000000
#> 166 2003:1:GFR:SOL:TVS:2024:27 55.0217 13.7897 Gadus morhua 2.0000000
#> 167 1994:1:GFR:SOL:H20:44:24 55.0333 13.4333 Gadus morhua 2.0000000
#> 168 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 169 2004:1:GFR:SOL:TVS:17:32 55.1985 14.3117 Gadus morhua 1.9354839
#> 170 2000:1:DEN:DAN2:GRT:64:31 56.3995 20.1068 Gadus morhua 1.0000000
#> 171 2000:4:DEN:DAN2:TVL:87:44 55.4463 18.5817 Gadus morhua 2.0000000
#> 172 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 173 2010:1:GFR:SOL2:TVS:24237:31 55.1092 14.1750 Gadus morhua 2.0000000
#> 174 1992:1:DEN:DAN2:GRT:9:6 54.6667 14.5000 Gadus morhua 1.0000000
#> 175 1996:1:SWE:ARG:FOT:90:39 57.0483 18.9283 Gadus morhua 2.0000000
#> 176 1997:4:SWE:ARG:FOT:754:24 55.8068 19.0093 Gadus morhua 2.0000000
#> 177 1999:4:LAT:AA36:LBT:2:8 56.3667 20.1333 Gadus morhua 2.0000000
#> 178 1995:1:DEN:DAN2:GRT:21:8 56.0500 17.5833 Gadus morhua 1.0000000
#> 179 1995:1:SWE:ARG:GOV:95:43 57.4500 16.9900 Gadus morhua 2.0000000
#> 180 1995:1:RUS:RUEK:DT:NA:4 55.5833 19.6167 Gadus morhua 2.0000000
#> 181 1995:4:SWE:ARG:FOT:250:5 55.5745 18.3732 Gadus morhua 2.0000000
#> 182 1991:1:DEN:DAN2:GRT:36:24 56.2500 17.9167 Gadus morhua 1.0000000
#> 183 1991:1:GFR:SOL:CHP:26071:48 54.9667 18.6000 Gadus morhua 1.0000000
#> 184 1993:1:GFR:SOL:H20:28:24 54.7000 14.1167 Gadus morhua 2.0000000
#> 185 1993:1:SWE:ARG:FOT:60:12 56.5178 16.8225 Gadus morhua 1.0000000
#> 186 2002:1:DEN:DAN2:TVL:133:55 55.4001 16.5374 Gadus morhua 2.0000000
#> 187 2002:4:DEN:DAN2:TVL:85:39 55.4737 20.0520 Gadus morhua 2.0000000
#> 188 1994:1:SWE:ARG:FOT:78:27 56.4717 18.6767 Gadus morhua 2.0000000
#> 189 2010:4:SWE:ARG:TVL:670:2 55.6737 14.4913 Gadus morhua 2.0000000
#> 190 2000:1:DEN:DAN2:GRT:26:13 55.9490 17.5745 Gadus morhua 1.0000000
#> 191 2000:1:SWE:ARG:GOV:220:21 55.0100 13.9300 Gadus morhua 2.0000000
#> 192 1996:1:DEN:DAN2:GRT:32:18 56.4650 18.7033 Gadus morhua 1.0000000
#> 193 1996:1:DEN:DAN2:GRT:50:28 56.4266 19.9616 Gadus morhua 1.0000000
#> 194 1992:1:GFR:SOL:CHP:2517:17 55.3000 16.2167 Gadus morhua 1.0000000
#> 195 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 196 1992:4:GFR:SOL:H20:28:38 54.7000 14.1000 Gadus morhua 2.0000000
#> 197 1997:1:DEN:DAN2:GRT:11:4 55.1550 16.4450 Gadus morhua 1.0000000
#> 198 1997:1:SWE:ARG:FOT:185:9 55.4583 14.4717 Gadus morhua 2.0000000
#> 199 1997:4:SWE:ARG:FOT:746:17 56.1283 17.5800 Gadus morhua 2.0000000
#> 200 2005:1:GFR:SOL2:TVS:24001:16 54.4178 12.3205 Gadus morhua 2.0000000
#> 201 2005:1:DEN:DAN2:TVL:108:10 55.0759 16.4263 Gadus morhua 2.0000000
#> 202 2005:4:DEN:DAN2:TVL:22:10 55.7027 18.6202 Gadus morhua 2.0000000
#> 203 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 204 1998:1:POL:BAL:P20:03Mar:55 54.7000 15.9667 Gadus morhua 2.0000000
#> 205 1998:1:SWE:ARG:FOT:230:31 57.3755 19.1868 Gadus morhua 2.0000000
#> 206 1998:4:SWE:ARG:FOT:718:20 55.9375 17.0503 Gadus morhua 2.0000000
#> 207 1998:4:SWE:ARG:FOT:720:22 56.0548 17.7505 Gadus morhua 2.0000000
#> 208 1999:1:DEN:DAN2:GRT:44:20 54.8683 15.5667 Gadus morhua 1.0000000
#> 209 1999:1:POL:BAL:P20:02Feb:14 54.8670 18.6500 Gadus morhua 2.0000000
#> 210 1995:1:LAT:RUEK:DT:000001:23 56.4833 20.0167 Gadus morhua 1.0000000
#> 211 1995:1:DEN:DAN2:GRT:157:59 54.9166 14.9333 Gadus morhua 1.0000000
#> 212 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 213 1991:1:GFR:SOL:CHP:2406:29 55.0500 13.3000 Gadus morhua 1.0000000
#> 214 1991:1:GFR:SOL:CHP:26071:48 54.9667 18.6000 Gadus morhua 1.0000000
#> 215 2003:4:DEN:DAN2:TVL:49:24 55.4697 15.5539 Gadus morhua 1.9354839
#> 216 2011:4:DEN:DAN2:TVL:39:42 55.7076 14.7245 Gadus morhua 2.0689655
#> 217 2002:4:GFR:SOL:TVS:43:33 55.2667 14.0333 Gadus morhua 2.0000000
#> 218 1994:1:DEN:DAN2:GRT:68:34 55.3667 18.3667 Gadus morhua 1.0000000
#> 219 2010:1:DEN:DAN2:TVL:100:1 55.0897 16.3814 Gadus morhua 2.0000000
#> 220 2010:1:DEN:DAN2:TVL:102:2 55.1465 16.0199 Gadus morhua 2.0000000
#> 221 2010:1:DEN:DAN2:TVL:124:5 55.2306 15.9489 Gadus morhua 2.0000000
#> 222 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 223 2010:1:DEN:DAN2:TVL:45:39 55.0349 15.2867 Gadus morhua 2.0000000
#> 224 2004:1:POL:BAL:TVL:31:31 54.8333 15.4333 Gadus morhua 2.0000000
#> 225 2004:4:RUS:ATL:TVL:NA:68 54.5683 19.6417 Gadus morhua 2.0000000
#> 226 2000:1:LAT:AA36:LBT:1:8 56.3500 19.7500 Gadus morhua 2.0000000
#> 227 2000:1:SWE:ARG:GOV:251:45 57.4717 17.5550 Gadus morhua 2.0000000
#> 228 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 2.0000000
#> 229 2007:4:POL:BAL:TVL:26132:1 54.5019 18.8678 Gadus morhua 2.0000000
#> 230 2009:1:DEN:DAN2:TVL:70:46 55.6334 15.5817 Gadus morhua 2.0000000
#> 231 2005:1:DEN:DAN2:TVL:108:10 55.0759 16.4263 Gadus morhua 2.0000000
#> 232 2008:4:DEN:DAN2:TVL:163:12 55.3397 16.2973 Gadus morhua 2.0000000
#> 233 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 5.0000000
#> 234 1998:1:POL:BAL:P20:01Jan:46 55.3833 17.2000 Gadus morhua 2.0000000
#> 235 1999:1:DEN:DAN2:GRT:69:32 56.3950 18.6800 Gadus morhua 1.0169492
#> 236 1999:1:DEN:DAN2:GRT:96:44 55.4967 18.4567 Gadus morhua 1.0169492
#> 237 1999:4:DEN:DAN2:TVL:100030:18 55.3833 16.7167 Gadus morhua 2.0000000
#> 238 2011:1:SWE:77MA:TVL:52:9 55.6872 15.0782 Gadus morhua 2.0000000
#> 239 2011:1:RUS:ATLD:TVL:56:40 55.3583 19.9267 Gadus morhua 2.0000000
#> 240 2011:4:DEN:DAN2:TVL:173:15 55.0737 16.4262 Gadus morhua 2.0000000
#> 241 1995:1:GFR:SOL:H20:32:31 54.7333 13.4000 Gadus morhua 2.0000000
#> 242 1995:1:GFR:SOL:H20:66:83 56.1000 17.6333 Gadus morhua 2.0000000
#> 243 2003:1:DEN:DAN2:TVL:91:47 55.9596 17.5814 Gadus morhua 2.0000000
#> 244 2003:4:GFR:SOL:TVS:24100:50 55.2083 13.1525 Gadus morhua 2.0000000
#> 245 2002:1:DEN:DAN2:TVL:8:4 55.2224 13.2880 Gadus morhua 2.0000000
#> 246 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 2.0000000
#> 247 1993:1:SWE:ARG:FOT:79:31 55.3282 16.0507 Gadus morhua 1.0000000
#> 248 1994:1:SWE:ARG:GOV:82:31 55.4583 14.5100 Gadus morhua 2.6000000
#> 249 1994:4:GFR:SOL:H20:33:53 54.7333 13.5000 Gadus morhua 4.0000000
#> 250 1991:1:GFR:SOL:CHP:2503:32 55.3167 15.0333 Gadus morhua 1.0000000
#> 251 2000:1:DEN:DAN2:GRT:30:15 55.9085 17.7397 Gadus morhua 1.0000000
#> 252 2000:1:GFR:SOL:H20:82:98 55.2500 17.3000 Gadus morhua 2.0000000
#> 253 2000:4:DEN:DAN2:TVL:80:41 55.3554 18.0697 Gadus morhua 2.0000000
#> 254 2007:4:GFR:SOL2:TVS:24047:43 54.6083 14.4135 Gadus morhua 2.0000000
#> 255 1996:1:DEN:DAN2:GRT:132:57 54.8650 13.8350 Gadus morhua 1.0000000
#> 256 1996:1:RUS:RUEK:DT:NA:17 55.7000 18.5500 Gadus morhua 3.0000000
#> 257 1996:1:SWE:ARG:FOT:76:25 55.5467 18.4150 Gadus morhua 2.0000000
#> 258 1997:1:SWE:ARG:FOT:204:25 57.2083 20.5867 Gadus morhua 2.0000000
#> 259 1997:4:LAT:AA36:LBT:2:19 56.0167 19.4333 Gadus morhua 1.0000000
#> 260 2008:1:LAT:BALL:TVL:1:30 55.7083 19.9733 Gadus morhua 2.0000000
#> 261 2008:4:DEN:DAN2:TVL:132:7 54.8132 14.9560 Gadus morhua 2.0000000
#> 262 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 263 1992:1:SWE:ARG:GOV:58:9 55.4517 14.6483 Gadus morhua 1.0000000
#> 264 2005:1:SWE:ARG:TVL:238:44 55.6655 14.9880 Gadus morhua 2.4000000
#> 265 2005:1:RUS:ATL:TVL:NA:23 55.3667 19.9333 Gadus morhua 2.0000000
#> 266 2005:4:POL:BAL:TVL:NA:34 55.2025 19.0336 Gadus morhua 2.0000000
#> 267 1998:1:DEN:DAN2:GRT:138:65 55.4433 18.3217 Gadus morhua 1.0000000
#> 268 1998:1:GFR:SOL:H20:78:85 55.5833 15.6167 Gadus morhua 2.0000000
#> 269 1998:1:SWE:ARG:FOT:207:15 55.9271 17.1108 Gadus morhua 2.0000000
#> 270 1999:1:DEN:DAN2:GRT:58:27 56.1950 17.9433 Gadus morhua 1.0000000
#> 271 1999:1:DEN:DAN2:GRT:54:25 56.0567 17.5933 Gadus morhua 1.0000000
#> 272 1999:1:GFR:SOL:H20:50:71 55.0333 13.6167 Gadus morhua 2.0000000
#> 273 1999:1:DEN:DAN2:TVL:151:88 54.7667 15.0000 Gadus morhua 2.0000000
#> 274 1999:1:SWE:ARG:FOT:214:21 55.0100 13.9183 Gadus morhua 2.0000000
#> 275 2011:1:POL:BAL:TVL:26182:32 55.0450 18.3300 Gadus morhua 6.0000000
#> 276 2003:1:RUS:ATL:TVL:NA:34 55.1167 20.4667 Gadus morhua 2.0000000
#> 277 2003:4:DEN:DAN2:TVL:80:31 54.9502 15.6187 Gadus morhua 2.0000000
#> 278 2002:1:DEN:DAN2:TVL:133:55 55.4001 16.5374 Gadus morhua 2.0000000
#> 279 2002:1:RUS:RUS6:TVL:NA:7 55.1167 20.4350 Gadus morhua 2.0000000
#> 280 2002:1:POL:BAL:TVL:15:15 55.4667 17.4167 Gadus morhua 2.0000000
#> 281 1995:1:DEN:DAN2:GRT:67:28 55.5833 19.7000 Gadus morhua 1.0000000
#> 282 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 1.0000000
#> 283 1995:4:SWE:ARG:FOT:252:7 56.2238 18.4445 Gadus morhua 2.0000000
#> 284 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 285 1993:1:DEN:DAN2:GRT:13:7 55.0333 13.7500 Gadus morhua 1.0000000
#> 286 1993:1:POL:AA36:P20:02Feb:37 55.0833 15.8333 Gadus morhua 2.0000000
#> 287 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 1.0000000
#> 288 1991:1:POL:AA36:P20:03Mar:19 54.8000 18.9500 Gadus morhua 2.0000000
#> 289 2004:1:GFR:SOL:TVS:24012:53 54.7647 13.4758 Gadus morhua 2.0000000
#> 290 2007:4:SWE:ARG:TVL:696:21 55.6549 14.5438 Gadus morhua 2.0000000
#> 291 1996:4:GFR:SOL:H20:25:68 54.7167 13.1167 Gadus morhua 2.0000000
#> 292 2009:1:POL:BAL:TVL:25056:16 54.7567 15.9450 Gadus morhua 2.0000000
#> 293 2005:1:DEN:DAN2:TVL:84:60 55.3307 16.2947 Gadus morhua 4.0000000
#> 294 2005:1:DEN:DAN2:TVL:8:57 54.8919 15.1647 Gadus morhua 2.0000000
#> 295 1997:1:POL:BAL:P20:01Jan:15 54.7333 19.2833 Gadus morhua 2.0000000
#> 296 1997:1:DEN:DAN2:GRT:64:30 54.9783 13.9233 Gadus morhua 1.0000000
#> 297 1997:1:POL:BAL:P20:03Mar:44 55.4167 17.1833 Gadus morhua 2.0000000
#> 298 1997:4:LAT:AA36:LBT:2:9 56.3167 19.7000 Gadus morhua 1.0000000
#> 299 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 300 1998:1:SWE:ARG:FOT:206:14 55.8513 17.6927 Gadus morhua 2.0000000
#> 301 1998:4:GFR:SOL:H20:35:75 54.6500 13.7833 Gadus morhua 2.0000000
#> 302 1999:1:DEN:DAN2:GRT:96:44 55.4967 18.4567 Gadus morhua 1.0169492
#> 303 2003:4:DEN:DAN2:TVL:81:32 54.9512 15.6165 Gadus morhua 2.0000000
#> 304 2003:4:RUS:ATLD:TVL:NA:66 55.3850 19.9483 Gadus morhua 2.0000000
#> 305 2002:4:SWE:ARG:TVL:575:13 55.9938 17.5843 Gadus morhua 2.0000000
#> 306 1994:1:SWE:ARG:FOT:60:9 55.8383 17.6967 Gadus morhua 2.0000000
#> 307 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 308 1995:4:SWE:ARG:FOT:267:22 55.6752 14.4827 Gadus morhua 2.0000000
#> 309 2010:1:RUS:ATL:TVL:60:17 55.3617 18.0833 Gadus morhua 2.0000000
#> 310 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 2.0000000
#> 311 1993:1:SWE:ARG:GOV:88:40 55.2100 13.2767 Gadus morhua 1.0000000
#> 312 1993:1:SWE:ARG:FOT:82:34 55.8733 16.0850 Gadus morhua 1.0000000
#> 313 1993:1:SWE:ARG:FOT:79:31 55.3282 16.0507 Gadus morhua 1.0000000
#> 314 2004:1:POL:BAL:TVL:2:2 55.2333 18.1667 Gadus morhua 2.0000000
#> 315 2004:4:POL:BAL:TVL:NA:8 54.7667 18.6833 Gadus morhua 2.0000000
#> 316 1991:1:DEN:DAN2:GRT:83:46 55.6000 19.4833 Gadus morhua 1.0000000
#> 317 1991:1:GFR:SOL:CHP:2602:43 56.1667 18.5167 Gadus morhua 1.0000000
#> 318 1991:1:GFR:SOL:CHP:2604:44 56.1833 18.9333 Gadus morhua 1.0000000
#> 319 2000:1:GFR:SOL:H20:69:84 55.8000 16.2000 Gadus morhua 2.0000000
#> 320 2000:1:DEN:DAN2:GRT:30:15 55.9085 17.7397 Gadus morhua 1.0000000
#> 321 2000:1:SWE:ARG:GOV:237:34 55.8467 15.5717 Gadus morhua 2.0000000
#> 322 2008:1:DEN:DAN2:TVL:83:49 55.5886 16.3974 Gadus morhua 1.9354839
#> 323 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 5.0000000
#> 324 1996:1:GFR:SOL:H20:82:113 55.2500 17.3333 Gadus morhua 2.0000000
#> 325 1996:4:GFR:SOL:H20:47:45 55.1500 14.2667 Gadus morhua 2.0000000
#> 326 1997:1:DEN:DAN2:GRT:22:9 55.9500 17.5850 Gadus morhua 1.0000000
#> 327 1997:1:SWE:ARG:FOT:198:20 56.0600 17.7583 Gadus morhua 2.0000000
#> 328 1997:4:SWE:ARG:FOT:756:26 56.2205 18.4318 Gadus morhua 2.0000000
#> 329 1992:1:SWE:ARG:FOT:74:25 57.0450 17.9650 Gadus morhua 1.0000000
#> 330 1998:1:DEN:DAN2:GRT:40:19 55.8917 17.7267 Gadus morhua 1.0000000
#> 331 2001:4:DEN:DAN2:TVL:76:35 55.2734 18.2922 Gadus morhua 2.0000000
#> 332 1999:4:LAT:AA36:LBT:2:8 56.3667 20.1333 Gadus morhua 2.0000000
#> 333 2011:4:DEN:DAN2:TVL:39:42 55.7076 14.7245 Gadus morhua 2.0689655
#> 334 2002:1:DEN:DAN2:TVL:8:4 55.2224 13.2880 Gadus morhua 2.0000000
#> 335 2002:4:SWE:ARG:TVL:574:12 56.1235 17.6527 Gadus morhua 2.0000000
#> 336 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 337 1994:1:SWE:ARG:FOT:76:25 57.0717 18.8350 Gadus morhua 2.0000000
#> 338 1994:4:SWE:ARG:FOT:265:10 55.7017 14.3900 Gadus morhua 2.0000000
#> 339 1995:1:LAT:RUEK:DT:000001:23 56.4833 20.0167 Gadus morhua 1.0000000
#> 340 1995:1:SWE:ARG:GOV:82:30 57.3617 19.1700 Gadus morhua 2.0000000
#> 341 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 1.0000000
#> 342 1993:1:SWE:ARG:GOV:88:40 55.2100 13.2767 Gadus morhua 1.0000000
#> 343 1993:4:GFR:SOL:H20:25:64 54.7167 13.1167 Gadus morhua 4.0000000
#> 344 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 345 2008:4:POL:BAL:TVL:26182:14 55.0433 18.3083 Gadus morhua 2.0000000
#> 346 2000:1:DEN:DAN2:GRT:68:33 55.3733 18.6138 Gadus morhua 1.0169492
#> 347 2000:1:SWE:ARG:GOV:235:32 55.8783 16.0750 Gadus morhua 2.0000000
#> 348 2000:4:SWE:ARG:GOV:579:13 55.2117 13.2650 Gadus morhua 2.0000000
#> 349 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 350 1991:1:GFR:SOL:CHP:25232:67 54.8000 15.2333 Gadus morhua 1.0000000
#> 351 2005:1:DEN:DAN2:TVL:20:25 55.0485 16.2891 Gadus morhua 2.0000000
#> 352 2005:1:DEN:DAN2:TVL:99:70 54.8067 14.9931 Gadus morhua 2.0000000
#> 353 2005:1:DEN:DAN2:TVL:26:28 55.2705 16.8948 Gadus morhua 2.0000000
#> 354 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 1.9354839
#> 355 2009:4:POL:BAL:TVL:NA:4 54.4333 19.3083 Gadus morhua 2.0000000
#> 356 1996:1:DEN:DAN2:GRT:76:41 55.1450 16.3883 Gadus morhua 1.0000000
#> 357 1996:1:DEN:DAN2:GRT:57:31 56.1383 19.1900 Gadus morhua 1.0000000
#> 358 1996:1:DEN:DAN2:GRT:65:35 55.5066 17.9516 Gadus morhua 1.0000000
#> 359 1996:1:SWE:ARG:FOT:77:26 55.7960 19.0145 Gadus morhua 2.0000000
#> 360 1997:1:RUS:ATL:HAK:NA:40 56.4667 20.0167 Gadus morhua 2.0000000
#> 361 1997:4:LAT:AA36:LBT:2:13 56.5167 20.4167 Gadus morhua 1.0000000
#> 362 1998:1:DEN:DAN2:GRT:91:43 56.4400 18.6067 Gadus morhua 1.0000000
#> 363 1998:1:DEN:DAN2:GRT:138:65 55.4433 18.3217 Gadus morhua 1.0000000
#> 364 1998:1:RUS:ATLD:HAK:NA:34 55.6167 19.7333 Gadus morhua 2.0000000
#> 365 1998:1:SWE:ARG:FOT:248:44 55.7975 15.9542 Gadus morhua 2.0000000
#> 366 1998:1:POL:BAL:P20:01Jan:39 55.4333 17.4333 Gadus morhua 2.0000000
#> 367 1998:1:SWE:ARG:FOT:206:14 55.8513 17.6927 Gadus morhua 2.0000000
#> 368 1998:1:RUS:ATLD:HAK:NA:16 54.9333 19.5500 Gadus morhua 2.0000000
#> 369 1998:4:SWE:ARG:FOT:731:29 57.8735 19.5127 Gadus morhua 2.0000000
#> 370 2001:1:DEN:DAN2:TVL:8:4 55.2114 13.5864 Gadus morhua 2.0000000
#> 371 2001:1:DEN:DAN2:TVL:56:27 55.4012 16.7389 Gadus morhua 2.0000000
#> 372 2001:4:DEN:DAN2:TVL:72:33 54.9801 17.4253 Gadus morhua 2.0000000
#> 373 1999:4:SWE:ARG:FOT:671:33 55.8150 15.3950 Gadus morhua 2.0000000
#> 374 1999:4:SWE:ARG:FOT:663:27 56.2300 18.4400 Gadus morhua 2.0000000
#> 375 2003:4:DEN:DAN2:TVL:13:6 55.0763 16.2384 Gadus morhua 2.0000000
#> 376 2010:4:DEN:DAN2:TVL:38:43 55.5351 17.5546 Gadus morhua 2.0000000
#> 377 2002:4:DEN:DAN2:TVL:77:34 55.1248 19.7450 Gadus morhua 2.0000000
#> 378 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 379 1994:1:SWE:ARG:GOV:91:40 55.5250 16.2950 Gadus morhua 2.0000000
#> 380 2004:1:SWE:ARG:TVL:252:23 56.7233 16.9915 Gadus morhua 2.0000000
#> 381 2007:4:GFR:SOL2:TVS:24300:51 54.8358 14.7603 Gadus morhua 2.0000000
#> 382 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 2.0000000
#> 383 1995:1:RUS:RUEK:DT:NA:14 54.9833 19.5333 Gadus morhua 2.0000000
#> 384 1995:4:SWE:ARG:FOT:252:7 56.2238 18.4445 Gadus morhua 2.0000000
#> 385 1993:1:DEN:DAN2:GRT:75:33 56.4500 18.6167 Gadus morhua 1.0000000
#> 386 1993:1:DEN:DAN2:GRT:79:37 56.4333 18.7167 Gadus morhua 1.0000000
#> 387 1993:1:POL:AA36:P20:02Feb:48 55.3333 17.3167 Gadus morhua 2.0000000
#> 388 1993:1:POL:AA36:P20:02Feb:50 55.4333 17.1667 Gadus morhua 2.0000000
#> 389 1993:1:SWE:ARG:FOT:79:31 55.3282 16.0507 Gadus morhua 1.0000000
#> 390 2012:4:DEN:DAN2:TVL:40:11 55.2367 17.2757 Gadus morhua 2.0000000
#> 391 2000:1:DEN:DAN2:TVL:158:79 55.9668 17.5793 Gadus morhua 2.0000000
#> 392 2000:1:DEN:DAN2:GRT:30:15 55.9085 17.7397 Gadus morhua 1.0000000
#> 393 2000:1:RUS:ATL:HAK:NA:15 55.1167 20.4500 Gadus morhua 2.0000000
#> 394 2005:4:POL:BAL:TVL:NA:30 54.4508 19.2847 Gadus morhua 2.0000000
#> 395 2009:1:DEN:DAN2:TVL:266:37 55.0795 16.4275 Gadus morhua 2.0000000
#> 396 2009:1:DEN:DAN2:TVL:274:40 55.2248 15.9445 Gadus morhua 2.0000000
#> 397 2009:1:SWE:ARG:TVL:260:46 55.4592 14.4789 Gadus morhua 2.0000000
#> 398 2009:4:DEN:DAN2:TVL:9:51 55.4633 14.5945 Gadus morhua 2.0000000
#> 399 2009:4:POL:BAL:TVL:NA:30 54.9350 18.5633 Gadus morhua 2.0000000
#> 400 1996:4:SWE:ARG:FOT:223:18 55.9350 17.0517 Gadus morhua 2.0000000
#> 401 1991:1:DEN:DAN2:GRT:120:60 55.0667 16.2167 Gadus morhua 1.0000000
#> 402 1991:1:LAT:90MX:LBT:000001:11 56.1167 20.5167 Gadus morhua 2.0000000
#> 403 1991:1:LAT:90MX:LBT:000001:19 55.6167 20.0833 Gadus morhua 2.0000000
#> 404 1991:4:GFR:SOL:H20:42:43 54.9500 13.1167 Gadus morhua 2.0000000
#> 405 1997:1:DEN:DAN2:GRT:56:26 55.4550 18.2833 Gadus morhua 1.0000000
#> 406 1997:1:POL:BAL:P20:01Jan:22 54.8833 18.6833 Gadus morhua 2.0000000
#> 407 1997:1:RUS:ATL:HAK:NA:18 54.6833 19.5000 Gadus morhua 2.0000000
#> 408 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 1.0000000
#> 409 1992:4:GFR:SOL:H20:25:23 54.7167 13.1167 Gadus morhua 5.0000000
#> 410 2011:1:DEN:DAN2:TVL:113:4 55.2371 17.2685 Gadus morhua 2.0000000
#> 411 1998:1:DEN:DAN2:GRT:80:39 54.7783 15.5050 Gadus morhua 1.0000000
#> 412 1998:1:GFR:SOL:H20:66:69 56.1000 17.6333 Gadus morhua 2.0000000
#> 413 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 414 1998:1:SWE:ARG:FOT:205:13 56.0820 17.7808 Gadus morhua 2.0000000
#> 415 1999:1:POL:BAL:P20:03Mar:70 54.5000 19.3167 Gadus morhua 2.0000000
#> 416 1999:1:POL:BAL:P20:02Feb:9 54.7500 19.0167 Gadus morhua 2.0000000
#> 417 1999:1:SWE:ARG:FOT:198:7 55.9267 17.1100 Gadus morhua 2.0000000
#> 418 2010:1:RUS:ATL:TVL:60:16 55.4683 18.3800 Gadus morhua 3.0000000
#> 419 2010:4:DEN:DAN2:TVL:78:48 55.2576 17.4246 Gadus morhua 1.9354839
#> 420 2003:1:DEN:DAN2:TVL:44:23 55.3196 17.2170 Gadus morhua 2.0000000
#> 421 2003:1:GFR:SOL:TVS:2024:27 55.0217 13.7897 Gadus morhua 4.0000000
#> 422 2003:1:SWE:ARG:TVL:219:2 55.7042 14.6728 Gadus morhua 2.0000000
#> 423 2002:1:SWE:ARG:TVL:185:10 55.8263 15.4325 Gadus morhua 2.0000000
#> 424 2002:1:SWE:ARG:TVL:180:5 55.8886 17.1483 Gadus morhua 2.0000000
#> 425 2002:4:SWE:ARG:TVL:588:22 55.6842 14.4563 Gadus morhua 2.0000000
#> 426 2007:1:RUS:ATL:TVL:52:3 54.8267 19.6617 Gadus morhua 2.0000000
#> 427 2007:4:DEN:DAN2:TVL:3:44 55.2781 15.2228 Gadus morhua 2.0000000
#> 428 2006:4:DEN:DAN2:TVL:65:29 55.1137 16.3815 Gadus morhua 2.0000000
#> 429 2008:1:DEN:DAN2:TVL:81:48 55.5946 16.6646 Gadus morhua 2.0000000
#> 430 2008:4:POL:BAL:TVL:26183:1 54.8600 18.6167 Gadus morhua 4.0000000
#> 431 2008:4:RUS:ATLD:TVL:51:27 55.0067 19.6750 Gadus morhua 2.0000000
#> 432 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 5.0000000
#> 433 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 1.0000000
#> 434 1995:1:RUS:RUEK:DT:NA:31 55.3500 19.1333 Gadus morhua 3.0000000
#> 435 1995:1:SWE:ARG:GOV:64:12 55.2817 16.9233 Gadus morhua 2.0000000
#> 436 2014:1:GFR:SOL2:TVS:25182:89 54.8477 15.2660 Gadus morhua 2.0000000
#> 437 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 1.0000000
#> 438 2005:1:DEN:DAN2:TVL:18:23 54.8671 15.4380 Gadus morhua 2.0000000
#> 439 2005:1:POL:BAL:TVL:4:4 54.5683 18.8150 Gadus morhua 2.0000000
#> 440 2005:4:DEN:DAN2:TVL:4:20 55.3455 17.1058 Gadus morhua 2.0000000
#> 441 2005:4:POL:BAL:TVL:NA:30 54.4508 19.2847 Gadus morhua 2.0000000
#> 442 2009:1:POL:BAL:TVL:25056:16 54.7567 15.9450 Gadus morhua 2.0000000
#> 443 2009:1:RUS:ATL:TVL:57:17 55.0767 19.6133 Gadus morhua 3.0000000
#> 444 2009:1:SWE:ARG:TVL:244:31 55.8287 16.4292 Gadus morhua 2.0000000
#> 445 2000:4:DEN:DAN2:TVL:80:41 55.3554 18.0697 Gadus morhua 2.0000000
#> 446 2000:4:SWE:ARG:GOV:611:42 56.9323 17.1785 Gadus morhua 2.0000000
#> 447 1996:1:DEN:DAN2:GRT:109:46 55.3066 15.9650 Gadus morhua 0.9836066
#> 448 1996:1:DEN:DAN2:GRT:111:47 55.2150 15.6083 Gadus morhua 1.0000000
#> 449 1996:1:DEN:DAN2:GRT:69:38 55.3816 18.1216 Gadus morhua 1.0000000
#> 450 1996:1:RUS:RUEK:DT:NA:23 55.2500 19.5667 Gadus morhua 2.0000000
#> 451 1996:1:SWE:ARG:FOT:73:22 55.5683 16.4433 Gadus morhua 2.0000000
#> 452 1996:1:SWE:ARG:FOT:99:48 56.0567 17.7533 Gadus morhua 2.0000000
#> 453 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 2.0000000
#> 454 1991:1:DEN:DAN2:GRT:69:37 56.4333 19.9500 Gadus morhua 1.0000000
#> 455 1991:1:DEN:DAN2:GRT:75:40 56.5333 19.9500 Gadus morhua 1.0000000
#> 456 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 457 1991:1:DEN:DAN2:GRT:82:45 55.6333 19.6000 Gadus morhua 1.0000000
#> 458 1991:1:GFR:SOL:CHP:26061:46 55.6000 18.8500 Gadus morhua 1.0000000
#> 459 1991:1:GFR:SOL:CHP:26071:48 54.9667 18.6000 Gadus morhua 1.0000000
#> 460 1991:1:GFR:SOL:CHP:2518:56 55.2833 16.1500 Gadus morhua 1.0000000
#> 461 1997:1:DEN:DAN2:GRT:112:49 55.8733 15.9667 Gadus morhua 1.0000000
#> 462 1997:1:DEN:DAN2:GRT:58:27 55.5500 17.9283 Gadus morhua 1.0000000
#> 463 1997:1:POL:BAL:P20:01Jan:43 55.3500 17.4667 Gadus morhua 2.0000000
#> 464 1997:1:DEN:DAN2:GRT:24:10 55.9083 17.7417 Gadus morhua 1.0000000
#> 465 1997:1:POL:BAL:P20:03Mar:45 55.3833 17.2000 Gadus morhua 2.0000000
#> 466 1997:4:SWE:ARG:FOT:754:24 55.8068 19.0093 Gadus morhua 4.0000000
#> 467 2011:1:DEN:DAN2:TVL:87:54 55.3761 16.9989 Gadus morhua 1.9354839
#> 468 1992:1:GFR:SOL:CHP:26011:28 56.1333 18.3000 Gadus morhua 1.0000000
#> 469 1992:1:GFR:SOL:CHP:26022:40 56.2000 18.5333 Gadus morhua 1.0000000
#> 470 1998:1:DEN:DAN2:GRT:105:49 57.0933 18.8400 Gadus morhua 1.0169492
#> 471 1998:1:DEN:DAN2:GRT:28:13 55.3917 17.3567 Gadus morhua 1.0000000
#> 472 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 473 1998:1:RUS:ATLD:HAK:NA:1 55.8000 20.5667 Gadus morhua 2.0000000
#> 474 1998:1:POL:BAL:P20:01Jan:17 54.9000 18.7333 Gadus morhua 2.0000000
#> 475 1998:1:RUS:ATLD:HAK:NA:35 55.5167 19.8833 Gadus morhua 6.0000000
#> 476 1998:1:RUS:ATLD:HAK:NA:37 55.5167 20.0333 Gadus morhua 2.0000000
#> 477 1999:1:POL:BAL:P20:03Mar:59 55.2000 18.9333 Gadus morhua 2.0000000
#> 478 2010:1:GFR:SOL2:TVS:24067:55 54.8217 13.4008 Gadus morhua 2.0000000
#> 479 2010:1:GFR:SOL2:TVS:24210:23 55.0145 13.3110 Gadus morhua 2.0000000
#> 480 2003:1:DEN:DAN2:TVL:71:36 55.3709 15.5140 Gadus morhua 2.0000000
#> 481 2003:1:GFR:SOL:TVS:2024:27 55.0217 13.7897 Gadus morhua 2.0000000
#> 482 2003:1:GFR:SOL:TVS:774:15 54.7833 12.3618 Gadus morhua 2.0000000
#> 483 2003:1:RUS:ATL:TVL:NA:8 54.6500 19.5667 Gadus morhua 2.0000000
#> 484 2003:4:DEN:DAN2:TVL:13:6 55.0763 16.2384 Gadus morhua 2.0000000
#> 485 2003:4:RUS:ATLD:TVL:NA:64 54.9200 19.5683 Gadus morhua 2.0000000
#> 486 2002:4:DEN:DAN2:TVL:13:6 55.4338 17.4729 Gadus morhua 2.0000000
#> 487 2002:4:SWE:ARG:TVL:581:17 55.8257 16.4458 Gadus morhua 2.0000000
#> 488 2002:4:SWE:ARG:TVL:576:14 55.9613 17.7718 Gadus morhua 3.3200000
#> 489 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 2.0000000
#> 490 2006:1:DEN:DAN2:TVL:46:25 55.0338 16.3414 Gadus morhua 2.0000000
#> 491 2006:1:RUS:ATLD:TVL:NA:25 55.7267 18.6450 Gadus morhua 2.0000000
#> 492 2006:4:DEN:DAN2:TVL:69:31 55.2607 17.4167 Gadus morhua 2.0000000
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#> 494 1994:1:GFR:SOL:H20:25:2 54.7333 13.0833 Gadus morhua 2.0000000
#> 495 1994:1:SWE:ARG:GOV:89:38 55.2117 13.6117 Gadus morhua 2.0000000
#> 496 1994:1:POL:BAL:P20:Jan:33 54.8667 18.6500 Gadus morhua 2.0000000
#> 497 2004:1:DEN:DAN2:TVL:82:41 55.1487 16.0115 Gadus morhua 2.0000000
#> 498 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 499 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 500 2012:1:DEN:DAN2:TVL:62:47 55.3807 15.2718 Gadus morhua 2.0000000
#> 501 2012:1:DEN:DAN2:TVL:172:14 55.3198 17.2292 Gadus morhua 2.0000000
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#> 503 1995:1:SWE:ARG:GOV:66:14 55.5733 18.3700 Gadus morhua 2.0000000
#> 504 2005:4:DEN:DAN2:TVL:22:10 55.7027 18.6202 Gadus morhua 2.0000000
#> 505 2009:4:DEN:DAN2:TVL:199:17 55.0098 16.2973 Gadus morhua 2.0689655
#> 506 2009:4:SWE:ARG:TVL:742:30 55.7141 14.4205 Gadus morhua 2.0000000
#> 507 2009:4:POL:BAL:TVL:25052:17 54.6467 16.1017 Gadus morhua 2.0000000
#> 508 2000:1:GFR:SOL:H20:45:55 55.0667 13.7333 Gadus morhua 2.0000000
#> 509 2000:1:RUS:ATL:HAK:NA:18 55.3000 19.9833 Gadus morhua 3.0000000
#> 510 2000:1:SWE:ARG:GOV:212:14 55.6850 14.4467 Gadus morhua 2.0000000
#> 511 2000:1:SWE:ARG:GOV:240:37 55.9350 17.0617 Gadus morhua 2.0000000
#> 512 2000:4:GFR:SOL:H20:50:65 55.0500 13.6667 Gadus morhua 2.0000000
#> 513 1993:1:DEN:DAN2:GRT:11:6 55.0500 13.3833 Gadus morhua 1.0000000
#> 514 1993:1:DEN:DAN2:GRT:95:43 57.0333 18.8167 Gadus morhua 1.0000000
#> 515 1993:1:POL:AA36:P20:02Feb:29 54.6500 19.2000 Gadus morhua 2.0000000
#> 516 1996:1:DEN:DAN2:GRT:57:31 56.1383 19.1900 Gadus morhua 1.0000000
#> 517 1996:1:RUS:RUEK:DT:NA:13 55.0833 18.4333 Gadus morhua 2.0000000
#> 518 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 2.0000000
#> 519 1997:1:POL:BAL:P20:01Jan:43 55.3500 17.4667 Gadus morhua 2.0000000
#> 520 1997:4:SWE:ARG:FOT:750:21 55.7965 15.8915 Gadus morhua 2.0000000
#> 521 1997:4:SWE:ARG:FOT:771:38 57.4668 17.5503 Gadus morhua 2.0000000
#> 522 1991:1:DEN:DAN2:GRT:8:7 55.0000 13.8167 Gadus morhua 1.0000000
#> 523 1991:1:GFR:SOL:CHP:2407:30 55.1000 13.7667 Gadus morhua 1.0000000
#> 524 1991:1:GFR:SOL:CHP:25274:74 54.6000 15.3000 Gadus morhua 1.0000000
#> 525 1991:1:POL:AA36:P20:01Jan:26 54.6500 19.2667 Gadus morhua 2.0000000
#> 526 2011:4:DEN:DAN2:TVL:175:16 55.0536 16.2955 Gadus morhua 2.0000000
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#> 528 2001:4:DEN:DAN2:TVL:73:34 55.2167 18.1222 Gadus morhua 2.0689655
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#> 530 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 531 1992:1:DEN:DAN2:GRT:60:43 56.3000 18.5500 Gadus morhua 1.0000000
#> 532 1998:1:DEN:DAN2:GRT:69:34 55.2100 15.1850 Gadus morhua 1.0000000
#> 533 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 534 1998:1:POL:BAL:P20:03Mar:67 55.4000 17.4333 Gadus morhua 2.0000000
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#> 536 1998:1:SWE:ARG:FOT:223:27 57.2170 20.6016 Gadus morhua 2.0000000
#> 537 1998:1:RUS:ATLD:HAK:NA:35 55.5167 19.8833 Gadus morhua 6.0000000
#> 538 1998:4:GFR:SOL:H20:30:73 54.5833 13.9333 Gadus morhua 2.0000000
#> 539 1999:1:POL:BAL:P20:03Mar:70 54.5000 19.3167 Gadus morhua 2.0000000
#> 540 1999:4:DEN:DAN2:TVL:100030:18 55.3833 16.7167 Gadus morhua 2.0000000
#> 541 1999:4:SWE:ARG:FOT:663:27 56.2300 18.4400 Gadus morhua 2.0000000
#> 542 2010:1:GFR:SOL2:TVS:24312:24 55.0438 13.4365 Gadus morhua 2.0000000
#> 543 2010:1:DEN:DAN2:TVL:143:8 55.5220 15.4943 Gadus morhua 2.0000000
#> 544 2010:1:DEN:DAN2:TVL:190:19 55.3558 16.2965 Gadus morhua 2.0000000
#> 545 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 546 2010:1:DEN:DAN2:TVL:24:32 55.4660 14.9670 Gadus morhua 2.0000000
#> 547 2010:1:GFR:SOL2:TVS:24237:31 55.1092 14.1750 Gadus morhua 2.0000000
#> 548 2010:4:DEN:DAN2:TVL:78:48 55.2576 17.4246 Gadus morhua 1.9354839
#> 549 2010:4:DEN:DAN2:TVL:194:22 54.8520 15.8379 Gadus morhua 2.0000000
#> 550 2010:4:RUS:ATLD:TVL:55:17 55.1067 19.7017 Gadus morhua 2.0000000
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#> 555 2006:1:RUS:ATLD:TVL:NA:3 54.8400 19.6600 Gadus morhua 2.0000000
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#> 559 2008:1:DEN:DAN2:TVL:185:22 55.6930 14.8571 Gadus morhua 2.0000000
#> 560 2008:1:POL:BAL:TVL:25061:15 54.8117 16.0217 Gadus morhua 4.0000000
#> 561 2008:1:POL:BAL:TVL:25062:16 54.9350 16.2217 Gadus morhua 2.0000000
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#> 563 2008:4:DEN:DAN2:TVL:132:7 54.8132 14.9560 Gadus morhua 2.0000000
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#> 565 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 566 2008:4:LAT:BALL:TVL:2:28 55.6550 20.2717 Gadus morhua 4.0000000
#> 567 2004:1:GFR:SOL:TVS:24202:15 54.6887 12.1988 Gadus morhua 2.0000000
#> 568 2004:4:DEN:DAN2:TVL:54:25 55.8723 16.4272 Gadus morhua 2.0000000
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#> 572 2012:4:POL:BAL:TVL:26020:34 54.7783 18.7133 Gadus morhua 2.0000000
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#> 574 2005:1:DEN:DAN2:TVL:39:34 55.3543 18.3801 Gadus morhua 2.0000000
#> 575 2005:1:DEN:DAN2:TVL:10:1 54.8874 15.8638 Gadus morhua 2.0000000
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#> 578 2005:4:POL:BAL:TVL:NA:35 55.1836 18.6181 Gadus morhua 2.0000000
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#> 585 2009:1:DEN:DAN2:TVL:262:35 55.3773 16.9970 Gadus morhua 2.0000000
#> 586 2009:1:DEN:DAN2:TVL:198:19 55.1238 16.3887 Gadus morhua 2.0689655
#> 587 2009:1:DEN:DAN2:TVL:266:37 55.0795 16.4275 Gadus morhua 2.0000000
#> 588 2009:1:RUS:ATL:TVL:57:33 55.6167 18.0817 Gadus morhua 2.0000000
#> 589 2009:1:SWE:ARG:TVL:259:45 55.4662 14.6059 Gadus morhua 2.0000000
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#> 594 2000:1:RUS:ATL:HAK:NA:29 55.5500 20.0667 Gadus morhua 2.0000000
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#> 603 1997:1:RUS:ATL:HAK:NA:26 55.1500 20.4500 Gadus morhua 2.0000000
#> 604 1997:4:SWE:ARG:FOT:744:15 55.8683 17.6617 Gadus morhua 2.0000000
#> 605 1997:4:SWE:ARG:FOT:754:24 55.8068 19.0093 Gadus morhua 2.0000000
#> 606 2011:1:DEN:DAN2:TVL:66:49 55.0873 16.3847 Gadus morhua 2.0000000
#> 607 2011:1:POL:BAL:TVL:26182:32 55.0450 18.3300 Gadus morhua 3.0000000
#> 608 2011:4:DEN:DAN2:TVL:173:15 55.0737 16.4262 Gadus morhua 2.0000000
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#> 610 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 1.0000000
#> 611 1991:1:DEN:DAN2:GRT:80:43 56.3333 19.6000 Gadus morhua 1.0000000
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#> 617 1998:1:DEN:DAN2:GRT:28:13 55.3917 17.3567 Gadus morhua 1.0000000
#> 618 1998:1:DEN:DAN2:GRT:131:62 55.6033 19.7117 Gadus morhua 1.0000000
#> 619 1998:1:RUS:ATLD:HAK:NA:36 55.3833 19.9167 Gadus morhua 4.0000000
#> 620 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 4.0000000
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#> 623 2007:1:POL:BAL:TVL:25394:29 54.6508 15.1681 Gadus morhua 2.0000000
#> 624 2007:4:DEN:DAN2:TVL:167:14 55.6271 16.6869 Gadus morhua 2.0000000
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#> 632 2003:1:DEN:DAN2:TVL:75:38 55.6298 15.5716 Gadus morhua 2.0000000
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#> 798 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 799 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 2.0000000
#> 800 1991:1:POL:AA36:P20:01Jan:27 54.6333 19.2500 Gadus morhua 2.0000000
#> 801 1991:1:LAT:90MX:LBT:000003:14 54.9167 19.5833 Gadus morhua 2.0000000
#> 802 1999:1:GFR:SOL:H20:61:89 55.9333 15.3000 Gadus morhua 2.0000000
#> 803 1999:1:POL:BAL:P20:02Feb:8 54.7670 18.9000 Gadus morhua 2.0000000
#> 804 1999:1:LAT:AA36:LBT:000001:5 56.5333 20.5167 Gadus morhua 1.0000000
#> 805 1999:4:DEN:DAN2:TVL:100004:2 55.8000 15.2833 Gadus morhua 2.0000000
#> 806 1999:4:SWE:ARG:FOT:658:23 56.1326 17.5733 Gadus morhua 2.0000000
#> 807 1999:4:LAT:AA36:LBT:2:14 56.6167 20.5500 Gadus morhua 8.0000000
#> 808 1999:4:LAT:AA36:LBT:2:8 56.3667 20.1333 Gadus morhua 2.0000000
#> 809 1992:1:DEN:DAN2:GRT:54:38 56.2833 18.5500 Gadus morhua 1.0000000
#> 810 1992:1:DEN:DAN2:GRT:61:44 56.8500 18.8833 Gadus morhua 1.0000000
#> 811 1992:1:GFR:SOL:CHP:28063:32 57.1833 20.6833 Gadus morhua 1.0000000
#> 812 1992:1:SWE:ARG:FOT:71:22 57.8083 18.1183 Gadus morhua 1.0000000
#> 813 2012:4:DEN:DAN2:TVL:29:10 55.0090 16.2954 Gadus morhua 2.0000000
#> 814 2012:4:DEN:DAN2:TVL:42:12 55.2600 17.4149 Gadus morhua 2.0000000
#> 815 2003:1:DEN:DAN2:TVL:80:41 55.5834 16.1936 Gadus morhua 2.0000000
#> 816 2003:4:DEN:DAN2:TVL:11:5 55.0830 16.4245 Gadus morhua 1.9354839
#> 817 2003:4:DEN:DAN2:TVL:81:32 54.9512 15.6165 Gadus morhua 2.0000000
#> 818 2003:4:SWE:ARG:TVL:736:26 55.8708 17.6608 Gadus morhua 2.0000000
#> 819 2013:1:DEN:DAN2:TVL:86:46 54.6766 15.6378 Gadus morhua 2.0000000
#> 820 2004:4:POL:BAL:TVL:NA:28 55.0667 17.0833 Gadus morhua 2.0000000
#> 821 2002:1:DEN:DAN2:TVL:133:55 55.4001 16.5374 Gadus morhua 2.0000000
#> 822 2002:1:DEN:DAN2:TVL:109:43 55.8357 17.8309 Gadus morhua 2.0000000
#> 823 2002:1:POL:BAL:TVL:16:16 55.4333 17.4833 Gadus morhua 2.0000000
#> 824 2002:1:RUS:RUS6:TVL:NA:12 54.8600 19.6567 Gadus morhua 2.0000000
#> 825 2002:4:DEN:DAN2:TVL:42:20 55.2357 16.7253 Gadus morhua 2.0000000
#> 826 1994:1:DEN:DAN2:GRT:64:33 55.3833 18.6167 Gadus morhua 1.0000000
#> 827 1994:1:SWE:ARG:GOV:82:31 55.4583 14.5100 Gadus morhua 2.6000000
#> 828 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 829 1994:1:SWE:ARG:FOT:65:14 56.0233 18.9167 Gadus morhua 2.0000000
#> 830 1994:1:SWE:ARG:FOT:60:9 55.8383 17.6967 Gadus morhua 2.0000000
#> 831 1994:1:POL:BAL:P20:Mar:5 54.7167 18.7500 Gadus morhua 2.0000000
#> 832 1994:4:SWE:ARG:FOT:281:26 57.1750 18.8600 Gadus morhua 2.0000000
#> 833 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 834 2005:1:DEN:DAN2:TVL:22:26 55.1330 16.3881 Gadus morhua 4.0000000
#> 835 2009:1:LAT:BALL:TVL:1:30 55.6417 20.1550 Gadus morhua 2.0000000
#> 836 2009:1:GFR:SOL2:TVS:24286:31 54.6667 14.6122 Gadus morhua 2.0000000
#> 837 2009:1:RUS:ATL:TVL:57:35 55.7267 18.6450 Gadus morhua 2.0000000
#> 838 2009:1:RUS:ATL:TVL:57:2 54.8983 19.5667 Gadus morhua 2.0000000
#> 839 2009:1:POL:BAL:TVL:26182:30 55.0483 18.3350 Gadus morhua 2.0000000
#> 840 2009:4:DEN:DAN2:TVL:129:5 55.4066 17.5854 Gadus morhua 2.0000000
#> 841 2009:4:DEN:DAN2:TVL:27:37 55.6664 14.9732 Gadus morhua 2.0000000
#> 842 2009:4:GFR:SOL2:TVS:24169:60 54.9255 13.0252 Gadus morhua 2.0000000
#> 843 2009:4:POL:BAL:TVL:25013:18 54.6183 16.2883 Gadus morhua 2.0000000
#> 844 1995:1:DEN:DAN2:GRT:23:9 56.1166 17.7333 Gadus morhua 1.0000000
#> 845 1995:1:DEN:DAN2:GRT:8:2 55.3833 16.7000 Gadus morhua 1.0169492
#> 846 1995:1:GFR:SOL:H20:31:18 54.6167 14.1000 Gadus morhua 2.0000000
#> 847 1995:1:GFR:SOL:H20:80:91 55.2833 16.1500 Gadus morhua 2.0000000
#> 848 1995:1:RUS:RUEK:DT:NA:7 55.3667 19.1000 Gadus morhua 2.0000000
#> 849 2000:1:GFR:SOL:H20:82:98 55.2500 17.3000 Gadus morhua 2.0000000
#> 850 2000:1:SWE:ARG:GOV:242:39 56.0717 17.7650 Gadus morhua 2.0000000
#> 851 1996:1:DEN:DAN2:GRT:32:18 56.4650 18.7033 Gadus morhua 1.0000000
#> 852 1996:1:DEN:DAN2:GRT:65:35 55.5066 17.9516 Gadus morhua 1.0000000
#> 853 1996:1:POL:BAL:P20:03Mar:20 54.7667 18.8833 Gadus morhua 2.0000000
#> 854 1996:1:LAT:RUEK:DT:000001:64 56.5167 20.2500 Gadus morhua 2.0000000
#> 855 1996:1:SWE:ARG:FOT:57:6 55.2100 13.2283 Gadus morhua 2.0000000
#> 856 1996:4:SWE:ARG:FOT:229:24 56.2267 18.4433 Gadus morhua 2.0000000
#> 857 2011:1:DEN:DAN2:TVL:87:54 55.3761 16.9989 Gadus morhua 1.9354839
#> 858 2011:1:POL:BAL:TVL:26182:32 55.0450 18.3300 Gadus morhua 6.0000000
#> 859 2011:1:RUS:ATLD:TVL:56:18 55.5083 17.9650 Gadus morhua 2.0000000
#> 860 2011:4:DEN:DAN2:TVL:173:15 55.0737 16.4262 Gadus morhua 2.0000000
#> 861 2011:4:DEN:DAN2:TVL:232:26 54.8262 15.2501 Gadus morhua 2.0000000
#> 862 1993:1:DEN:DAN2:GRT:17:9 55.0333 14.2167 Gadus morhua 1.0000000
#> 863 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 2.0000000
#> 864 1997:1:DEN:DAN2:GRT:56:26 55.4550 18.2833 Gadus morhua 1.0000000
#> 865 1997:1:POL:BAL:P20:01Jan:30 54.7500 18.7500 Gadus morhua 2.0000000
#> 866 1997:1:POL:BAL:P20:01Jan:31 54.7167 18.7667 Gadus morhua 2.0000000
#> 867 1997:1:DEN:DAN2:GRT:88:41 54.8150 16.0300 Gadus morhua 1.0000000
#> 868 1997:1:SWE:ARG:FOT:192:14 55.5683 16.4517 Gadus morhua 2.0000000
#> 869 1997:4:SWE:ARG:FOT:744:15 55.8683 17.6617 Gadus morhua 4.0000000
#> 870 2010:1:DEN:DAN2:TVL:98:48 55.0102 16.2765 Gadus morhua 2.0000000
#> 871 2010:1:DEN:DAN2:TVL:190:19 55.3558 16.2965 Gadus morhua 2.0000000
#> 872 2010:1:DEN:DAN2:TVL:207:20 55.2584 17.4180 Gadus morhua 2.0000000
#> 873 2010:4:DEN:DAN2:TVL:118:5 54.8186 15.9098 Gadus morhua 1.9354839
#> 874 2010:4:RUS:ATLD:TVL:55:17 55.1067 19.7017 Gadus morhua 2.0000000
#> 875 2008:1:DEN:DAN2:TVL:35:38 55.3900 17.5519 Gadus morhua 2.4000000
#> 876 2008:1:DEN:DAN2:TVL:133:9 54.8465 15.4528 Gadus morhua 2.0000000
#> 877 2008:4:DEN:DAN2:TVL:155:10 55.3473 17.1282 Gadus morhua 2.0000000
#> 878 2008:4:DEN:DAN2:TVL:157:11 55.3356 17.4120 Gadus morhua 2.0000000
#> 879 2007:1:POL:BAL:TVL:26020:1 54.8003 18.6853 Gadus morhua 2.0000000
#> 880 2007:4:GFR:SOL2:TVS:24152:56 54.8382 13.2672 Gadus morhua 2.0000000
#> 881 2007:4:DEN:DAN2:TVL:3:44 55.2781 15.2228 Gadus morhua 2.0000000
#> 882 2007:4:RUS:ATL:TVL:55:35 54.5433 19.6250 Gadus morhua 2.0000000
#> 883 2001:1:DEN:DAN2:TVL:131:54 55.6835 14.7934 Gadus morhua 2.0000000
#> 884 2006:1:DEN:DAN2:TVL:19:10 55.4011 17.4079 Gadus morhua 2.0000000
#> 885 2006:4:POL:BAL:TVL:NA:29 55.2347 17.7672 Gadus morhua 2.0000000
#> 886 1998:1:GFR:SOL:H20:45:49 55.0667 13.7333 Gadus morhua 2.0000000
#> 887 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 2.0000000
#> 888 1998:1:DEN:DAN2:GRT:44:21 56.0583 17.5983 Gadus morhua 1.0000000
#> 889 1998:1:POL:BAL:P20:03Mar:56 54.6667 16.1667 Gadus morhua 2.0000000
#> 890 1998:1:SWE:ARG:FOT:228:29 57.8751 19.5121 Gadus morhua 2.0000000
#> 891 1999:1:DEN:DAN2:GRT:111:52 55.0817 16.2650 Gadus morhua 2.0000000
#> 892 1999:1:DEN:DAN2:GRT:52:24 55.9533 17.5817 Gadus morhua 1.0000000
#> 893 1999:1:GFR:SOL:H20:76:131 55.3333 16.3167 Gadus morhua 2.0000000
#> 894 1999:1:RUS:ATL:HAK:NA:31 55.5333 20.0333 Gadus morhua 2.0000000
#> 895 1999:1:POL:BAL:P20:03Mar:70 54.5000 19.3167 Gadus morhua 2.0000000
#> 896 1999:1:POL:BAL:P20:02Feb:25 54.8830 15.6833 Gadus morhua 2.0000000
#> 897 1999:1:SWE:ARG:FOT:269:69 57.1180 17.2882 Gadus morhua 2.0000000
#> 898 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 1.0000000
#> 899 1991:1:GFR:SOL:CHP:2604:44 56.1833 18.9333 Gadus morhua 1.0000000
#> 900 1991:1:LAT:90MX:LBT:000001:12 55.1167 20.3333 Gadus morhua 1.0000000
#> 901 1991:1:GFR:SOL:CHP:26071:48 54.9667 18.6000 Gadus morhua 1.0000000
#> 902 1991:1:GFR:SOL:CHP:2516:54 55.3833 16.3500 Gadus morhua 1.0000000
#> 903 1991:1:LAT:90MX:LBT:000001:19 55.6167 20.0833 Gadus morhua 2.0000000
#> 904 1991:1:POL:AA36:P20:03Mar:1 54.7167 19.2000 Gadus morhua 2.0000000
#> 905 1991:1:LAT:90MX:LBT:000003:21 55.1167 19.4000 Gadus morhua 2.0000000
#> 906 1991:1:POL:AA36:P20:01Jan:28 54.9000 18.8000 Gadus morhua 2.0000000
#> 907 1992:1:GFR:SOL:CHP:25081:21 55.5833 15.8833 Gadus morhua 1.0000000
#> 908 1992:1:GFR:SOL:CHP:2511:24 55.8500 16.4167 Gadus morhua 1.0000000
#> 909 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 910 2003:1:DEN:DAN2:TVL:71:36 55.3709 15.5140 Gadus morhua 2.0000000
#> 911 2003:1:DEN:DAN2:TVL:91:47 55.9596 17.5814 Gadus morhua 2.0000000
#> 912 2002:1:GFR:SOL:TVS:923:173 54.9167 13.7667 Gadus morhua 2.0000000
#> 913 2002:1:SWE:ARG:TVL:195:20 56.4303 16.7683 Gadus morhua 2.0000000
#> 914 2002:4:SWE:ARG:TVL:570:9 56.5572 16.9162 Gadus morhua 2.0000000
#> 915 1994:1:DEN:DAN2:GRT:23:13 56.8500 18.8667 Gadus morhua 1.0000000
#> 916 1994:1:DEN:DAN2:GRT:64:33 55.3833 18.6167 Gadus morhua 1.0000000
#> 917 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 2.0000000
#> 918 1994:1:POL:BAL:P20:Mar:39 55.2833 17.2833 Gadus morhua 2.0000000
#> 919 1994:1:POL:BAL:P20:Mar:40 55.3000 17.6000 Gadus morhua 4.0000000
#> 920 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 921 2005:1:GFR:SOL2:TVS:24041:46 54.6248 14.3828 Gadus morhua 2.0000000
#> 922 2005:1:POL:BAL:TVL:34:34 54.4417 19.2717 Gadus morhua 3.0000000
#> 923 2005:1:POL:BAL:TVL:4:4 54.5683 18.8150 Gadus morhua 2.0000000
#> 924 2005:1:RUS:ATL:TVL:NA:23 55.3667 19.9333 Gadus morhua 2.0000000
#> 925 2005:4:RUS:ATLD:TVL:36:23 54.5717 19.6433 Gadus morhua 2.0000000
#> 926 2005:4:POL:BAL:TVL:NA:30 54.4508 19.2847 Gadus morhua 2.0000000
#> 927 2009:1:DEN:DAN2:TVL:120:4 55.3148 15.3390 Gadus morhua 2.0000000
#> 928 2009:1:DEN:DAN2:TVL:146:10 54.9568 15.5324 Gadus morhua 2.0000000
#> 929 2009:1:RUS:ATL:TVL:57:4 55.1083 19.7017 Gadus morhua 10.0000000
#> 930 2009:4:DEN:DAN2:TVL:78:48 55.8079 16.5230 Gadus morhua 2.0000000
#> 931 2009:4:DEN:DAN2:TVL:9:51 55.4633 14.5945 Gadus morhua 2.0000000
#> 932 2009:4:DEN:DAN2:TVL:176:14 55.0376 17.0136 Gadus morhua 2.0000000
#> 933 2009:4:SWE:ARG:TVL:739:27 55.4609 14.5249 Gadus morhua 2.0000000
#> 934 2009:4:POL:BAL:TVL:26186:2 54.4067 19.2733 Gadus morhua 2.0000000
#> 935 2009:4:POL:BAL:TVL:NA:27 54.4200 19.0333 Gadus morhua 2.0000000
#> 936 2000:1:DEN:DAN2:GRT:78:38 55.5005 17.4817 Gadus morhua 1.0000000
#> 937 2000:1:POL:BAL:P20:NA:57 54.8667 18.6667 Gadus morhua 2.0000000
#> 938 2000:4:LAT:AA36:LBT:2:17 56.6000 20.6833 Gadus morhua 2.0000000
#> 939 1995:1:DEN:DAN2:GRT:29:12 56.3833 18.5833 Gadus morhua 1.0000000
#> 940 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 1.0000000
#> 941 1995:1:DEN:DAN2:GRT:165:63 54.9166 13.6000 Gadus morhua 1.0000000
#> 942 1995:1:SWE:ARG:GOV:66:14 55.5733 18.3700 Gadus morhua 2.0000000
#> 943 1995:4:SWE:ARG:FOT:257:12 57.3613 19.1700 Gadus morhua 2.0000000
#> 944 2011:1:GFR:SOL2:TVS:24212:24 54.9937 13.3497 Gadus morhua 2.0000000
#> 945 2011:4:POL:BAL:TVL:25051:16 54.6600 15.9067 Gadus morhua 2.0000000
#> 946 1996:1:DEN:DAN2:GRT:46:26 56.4433 19.9866 Gadus morhua 1.0000000
#> 947 1996:1:GFR:SOL:H20:59:95 54.4167 16.0000 Gadus morhua 2.0000000
#> 948 1996:1:RUS:RUEK:DT:NA:17 55.7000 18.5500 Gadus morhua 3.0000000
#> 949 1996:1:POL:BAL:P20:01Jan:45 55.3500 17.0667 Gadus morhua 2.0000000
#> 950 1996:1:SWE:ARG:FOT:74:23 55.6700 16.4667 Gadus morhua 2.0000000
#> 951 1996:1:SWE:ARG:FOT:75:24 55.9350 17.0533 Gadus morhua 2.0000000
#> 952 1997:1:SWE:ARG:FOT:198:20 56.0600 17.7583 Gadus morhua 2.0000000
#> 953 1997:4:LAT:AA36:LBT:2:19 56.0167 19.4333 Gadus morhua 1.0000000
#> 954 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 1.0000000
#> 955 1997:4:SWE:ARG:FOT:753:23 55.5595 18.3875 Gadus morhua 2.0000000
#> 956 1997:4:SWE:ARG:FOT:754:24 55.8068 19.0093 Gadus morhua 2.0000000
#> 957 1993:1:GFR:SOL:H20:78:47 55.6000 15.7000 Gadus morhua 2.0000000
#> 958 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 1.0000000
#> 959 1993:1:SWE:ARG:FOT:82:34 55.8733 16.0850 Gadus morhua 1.0000000
#> 960 1993:1:SWE:ARG:FOT:58:10 56.0352 17.7188 Gadus morhua 1.0000000
#> 961 1993:1:SWE:ARG:FOT:80:32 55.4120 15.3205 Gadus morhua 1.0000000
#> 962 2010:1:DEN:DAN2:TVL:173:13 55.6681 14.7081 Gadus morhua 2.0000000
#> 963 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 964 2010:1:GFR:SOL2:TVS:24104:22 55.0662 13.3385 Gadus morhua 2.0000000
#> 965 2010:1:RUS:ATL:TVL:60:16 55.4683 18.3800 Gadus morhua 3.0000000
#> 966 2010:1:RUS:ATL:TVL:60:23 54.9217 19.5692 Gadus morhua 16.0000000
#> 967 2010:1:SWE:ARG:TVL:240:40 55.6522 14.6515 Gadus morhua 2.0000000
#> 968 2010:4:DEN:DAN2:TVL:118:5 54.8186 15.9098 Gadus morhua 1.9354839
#> 969 2010:4:DEN:DAN2:TVL:59:46 55.2593 17.3127 Gadus morhua 4.0000000
#> 970 2010:4:DEN:DAN2:TVL:142:11 54.5437 15.4478 Gadus morhua 2.0000000
#> 971 2010:4:RUS:ATLD:TVL:55:7 55.1000 20.1517 Gadus morhua 3.0000000
#> 972 2008:1:RUS:ATLD:TVL:49:2 55.1867 20.0333 Gadus morhua 13.0000000
#> 973 2008:1:RUS:ATLD:TVL:49:13 55.3650 19.9333 Gadus morhua 3.0000000
#> 974 2008:4:LTU:DAR:TVS:26052:2 55.5300 20.6100 Gadus morhua 1.0000000
#> 975 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 976 2008:4:POL:BAL:TVL:26037:2 54.8850 18.6667 Gadus morhua 4.0000000
#> 977 2008:4:POL:BAL:TVL:26020:18 54.9450 18.7100 Gadus morhua 4.0000000
#> 978 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 979 2007:1:DEN:DAN2:TVL:44:23 55.5981 16.6682 Gadus morhua 2.0000000
#> 980 2007:4:LTU:DAR:TVS:Nov:2 55.6000 20.0500 Gadus morhua 2.0000000
#> 981 2007:4:DEN:DAN2:TVL:3:44 55.2781 15.2228 Gadus morhua 2.0000000
#> 982 2007:4:POL:BAL:TVL:26132:1 54.5019 18.8678 Gadus morhua 2.0000000
#> 983 2006:4:POL:BAL:TVL:25017:10 54.7336 16.8514 Gadus morhua 2.0000000
#> 984 2001:1:SWE:ARG:TVL:231:25 57.1042 18.8748 Gadus morhua 2.0000000
#> 985 2001:1:RUS:ATL:TVL:NA:51 56.4000 20.0500 Gadus morhua 2.0000000
#> 986 2001:1:POL:BAL:P20:NA:11 54.4500 19.3167 Gadus morhua 2.0000000
#> 987 2001:4:DEN:DAN2:TVL:83:37 55.6627 18.0414 Gadus morhua 1.9354839
#> 988 2001:4:DEN:DAN2:TVL:4:3 55.2699 15.0100 Gadus morhua 2.0000000
#> 989 2012:1:DEN:DAN2:TVL:66:49 55.3799 15.5013 Gadus morhua 1.9354839
#> 990 1998:1:RUS:ATLD:HAK:NA:36 55.3833 19.9167 Gadus morhua 4.0000000
#> 991 2013:1:POL:BAL:TVL:25054:15 54.7267 15.7717 Gadus morhua 6.0000000
#> 992 2013:4:POL:BAL:TVL:25051:12 54.6450 15.9017 Gadus morhua 8.0000000
#> 993 2004:1:SWE:ARG:TVL:229:3 56.0957 18.0390 Gadus morhua 2.0000000
#> 994 2004:1:SWE:ARG:TVL:228:2 56.1137 17.7748 Gadus morhua 2.0000000
#> 995 2004:1:POL:BAL:TVL:42:42 55.0000 18.4500 Gadus morhua 2.0000000
#> 996 2004:4:DEN:DAN2:TVL:30:12 55.5016 18.5480 Gadus morhua 1.9354839
#> 997 1999:1:GFR:SOL:H20:42:65 54.9167 13.1167 Gadus morhua 2.0000000
#> 998 1999:1:GFR:SOL:H20:44:69 55.0333 13.4000 Gadus morhua 2.0000000
#> 999 1999:1:LAT:AA36:LBT:000001:8 56.3500 20.0167 Gadus morhua 1.0000000
#> 1000 1999:4:SWE:ARG:GOV:652:17 55.8400 15.5600 Gadus morhua 2.0000000
#> 1001 1999:4:LAT:AA36:LBT:2:8 56.3667 20.1333 Gadus morhua 2.0000000
#> 1002 2003:1:SWE:ARG:TVL:239:16 55.9857 17.1807 Gadus morhua 2.0000000
#> 1003 2003:4:DEN:DAN2:TVL:32:15 55.6290 16.2536 Gadus morhua 2.0000000
#> 1004 2003:4:DEN:DAN2:TVL:49:24 55.4697 15.5539 Gadus morhua 1.9354839
#> 1005 2003:4:DEN:DAN2:TVL:41:20 55.2569 17.3596 Gadus morhua 2.0000000
#> 1006 2002:1:DEN:DAN2:TVL:48:27 55.5493 16.5668 Gadus morhua 2.0000000
#> 1007 2002:1:RUS:RUS6:TVL:NA:31 55.5217 20.0017 Gadus morhua 3.0000000
#> 1008 2002:4:SWE:ARG:TVL:588:22 55.6842 14.4563 Gadus morhua 2.0000000
#> 1009 1992:1:DEN:DAN2:GRT:54:38 56.2833 18.5500 Gadus morhua 1.0000000
#> 1010 1992:1:DEN:DAN2:GRT:82:57 55.2667 16.0500 Gadus morhua 1.0000000
#> 1011 1992:1:GFR:SOL:CHP:2407:48 55.1000 13.9000 Gadus morhua 1.0000000
#> 1012 1992:1:DEN:DAN2:GRT:1:1 55.1333 12.7833 Gadus morhua 1.0000000
#> 1013 1992:1:GFR:SOL:CHP:25082:44 55.5500 15.5833 Gadus morhua 1.0000000
#> 1014 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 2.0000000
#> 1015 1991:1:DEN:DAN2:GRT:30:20 55.9500 17.2167 Gadus morhua 1.0000000
#> 1016 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 1.0000000
#> 1017 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 1.0000000
#> 1018 1991:1:DEN:DAN2:GRT:80:43 56.3333 19.6000 Gadus morhua 1.0000000
#> 1019 1991:1:GFR:SOL:CHP:2406:29 55.0500 13.3000 Gadus morhua 1.0000000
#> 1020 1991:1:GFR:SOL:CHP:2509:35 55.6833 16.0667 Gadus morhua 1.0000000
#> 1021 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 1022 1991:1:GFR:SOL:CHP:26061:46 55.6000 18.8500 Gadus morhua 1.0000000
#> 1023 2005:1:DEN:DAN2:TVL:53:43 55.2857 14.3436 Gadus morhua 2.0000000
#> 1024 2005:1:GFR:SOL2:TVS:24071:50 54.7532 13.9460 Gadus morhua 2.0000000
#> 1025 2005:1:DEN:DAN2:TVL:95:66 55.0966 15.2680 Gadus morhua 2.0000000
#> 1026 2005:1:SWE:ARG:TVL:224:32 55.7690 16.3343 Gadus morhua 2.0000000
#> 1027 2005:4:RUS:ATLD:TVL:36:27 55.1083 19.9183 Gadus morhua 2.0000000
#> 1028 2009:1:POL:BAL:TVL:25056:16 54.7567 15.9450 Gadus morhua 2.0000000
#> 1029 2009:1:RUS:ATL:TVL:57:2 54.8983 19.5667 Gadus morhua 2.0000000
#> 1030 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 1.9354839
#> 1031 2009:4:DEN:DAN2:TVL:250:28 54.7865 15.3003 Gadus morhua 2.0000000
#> 1032 2009:4:DEN:DAN2:TVL:226:23 54.7553 15.9528 Gadus morhua 1.9354839
#> 1033 2000:1:SWE:ARG:GOV:248:42 57.0767 18.8867 Gadus morhua 2.0000000
#> 1034 2000:4:DEN:DAN2:TVL:50:25 55.5048 17.8646 Gadus morhua 2.0000000
#> 1035 2000:4:SWE:ARG:GOV:584:18 55.8150 15.3917 Gadus morhua 2.0000000
#> 1036 2011:1:DEN:DAN2:TVL:16:16 54.8186 15.3228 Gadus morhua 2.0000000
#> 1037 2011:1:DEN:DAN2:TVL:140:12 55.2900 14.3554 Gadus morhua 2.0000000
#> 1038 2011:1:POL:BAL:TVL:25173:19 54.6533 15.5683 Gadus morhua 2.0000000
#> 1039 1995:1:GFR:SOL:H20:26:4 54.7000 13.2000 Gadus morhua 2.0000000
#> 1040 1995:1:DEN:DAN2:GRT:57:23 56.3666 19.8666 Gadus morhua 1.0000000
#> 1041 1995:1:DEN:DAN2:GRT:76:32 55.5000 17.9166 Gadus morhua 1.0000000
#> 1042 1995:1:LAT:RUEK:DT:000001:23 56.4833 20.0167 Gadus morhua 1.0000000
#> 1043 1995:1:LAT:RUEK:DT:000001:10 57.2833 20.6167 Gadus morhua 2.0000000
#> 1044 1995:1:LAT:RUEK:DT:000001:11 57.2167 20.6833 Gadus morhua 1.0000000
#> 1045 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 1.0000000
#> 1046 1995:1:DEN:DAN2:GRT:61:25 55.4666 18.3833 Gadus morhua 1.0000000
#> 1047 1995:1:DEN:DAN2:GRT:88:34 54.7166 14.9500 Gadus morhua 1.0000000
#> 1048 1995:4:SWE:ARG:FOT:257:12 57.3613 19.1700 Gadus morhua 2.0000000
#> 1049 1996:1:DEN:DAN2:GRT:133:58 54.9116 13.6416 Gadus morhua 1.0000000
#> 1050 1996:1:DEN:DAN2:GRT:28:15 56.3133 18.5783 Gadus morhua 1.0000000
#> 1051 1996:1:RUS:RUEK:DT:NA:8 54.9167 19.5333 Gadus morhua 2.0000000
#> 1052 1996:1:SWE:ARG:FOT:96:45 57.4583 17.0933 Gadus morhua 2.0000000
#> 1053 1996:1:RUS:RUEK:DT:NA:26 55.0500 19.7333 Gadus morhua 2.0000000
#> 1054 1996:1:SWE:ARG:FOT:71:20 55.8717 16.0683 Gadus morhua 2.0000000
#> 1055 1996:1:SWE:ARG:FOT:95:44 57.4800 17.5533 Gadus morhua 2.0000000
#> 1056 1996:1:SWE:ARG:FOT:58:7 55.2100 13.5767 Gadus morhua 2.0000000
#> 1057 2010:1:DEN:DAN2:TVL:100:1 55.0897 16.3814 Gadus morhua 2.0000000
#> 1058 2010:1:DEN:DAN2:TVL:124:5 55.2306 15.9489 Gadus morhua 2.0000000
#> 1059 2010:1:RUS:ATL:TVL:60:23 54.9217 19.5692 Gadus morhua 16.0000000
#> 1060 2010:4:DEN:DAN2:TVL:197:24 55.0354 16.2565 Gadus morhua 2.0000000
#> 1061 2010:4:DEN:DAN2:TVL:124:9 54.7532 15.9475 Gadus morhua 2.0689655
#> 1062 2008:1:DEN:DAN2:TVL:58:43 55.3458 17.1291 Gadus morhua 2.0000000
#> 1063 2008:1:GFR:SOL2:TVS:24107:46 55.2710 13.7397 Gadus morhua 2.0000000
#> 1064 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 1065 2008:4:SWE:ARG:TVL:717:23 55.9382 15.4028 Gadus morhua 2.0000000
#> 1066 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 11.0000000
#> 1067 1997:1:DEN:DAN2:GRT:18:7 55.6783 16.7883 Gadus morhua 1.0000000
#> 1068 1997:1:SWE:ARG:FOT:174:1 55.9717 15.4100 Gadus morhua 2.0000000
#> 1069 1997:1:SWE:ARG:FOT:201:23 55.8150 18.9833 Gadus morhua 2.0000000
#> 1070 1997:1:SWE:ARG:FOT:227:41 57.4783 17.0700 Gadus morhua 2.0000000
#> 1071 1997:1:SWE:ARG:FOT:197:19 55.9333 17.0500 Gadus morhua 2.0000000
#> 1072 1997:4:SWE:ARG:FOT:743:14 55.9367 17.0533 Gadus morhua 2.0000000
#> 1073 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 2.0000000
#> 1074 1997:4:GFR:SOL:H20:25:71 54.7167 13.1167 Gadus morhua 2.0000000
#> 1075 2007:1:LTU:DAR:TVS:Mar:4 55.4700 20.1100 Gadus morhua 2.0000000
#> 1076 2007:1:POL:BAL:TVL:25060:17 54.8508 16.0508 Gadus morhua 2.0000000
#> 1077 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 6.0000000
#> 1078 2006:1:DEN:DAN2:TVL:2:11 55.3990 17.7860 Gadus morhua 2.0000000
#> 1079 2006:1:DEN:DAN2:TVL:67:36 55.0806 15.6429 Gadus morhua 2.0000000
#> 1080 2006:1:POL:BAL:TVL:25175:17 54.6683 15.6342 Gadus morhua 2.0000000
#> 1081 2006:4:DEN:DAN2:TVL:53:23 55.8637 16.4367 Gadus morhua 2.0000000
#> 1082 2006:4:DEN:DAN2:TVL:101:1 55.6026 14.5747 Gadus morhua 2.0000000
#> 1083 1993:1:GFR:SOL:H20:40:12 54.9167 13.6167 Gadus morhua 2.0000000
#> 1084 1993:1:GFR:SOL:H20:41:13 54.8667 13.2167 Gadus morhua 2.0000000
#> 1085 1993:1:SWE:ARG:FOT:57:9 55.8015 17.7367 Gadus morhua 1.0000000
#> 1086 1993:4:SWE:ARG:FOT:252:21 56.1133 17.5917 Gadus morhua 3.0000000
#> 1087 2001:1:DEN:DAN2:TVL:38:19 55.8907 17.1259 Gadus morhua 2.0000000
#> 1088 2012:1:DEN:DAN2:TVL:220:40 55.6654 14.9732 Gadus morhua 2.0000000
#> 1089 2012:4:DEN:DAN2:TVL:40:11 55.2367 17.2757 Gadus morhua 2.0000000
#> 1090 2013:1:DEN:DAN2:TVL:36:30 55.4811 15.2300 Gadus morhua 2.0000000
#> 1091 1998:1:DEN:DAN2:GRT:36:17 55.8967 17.0650 Gadus morhua 1.0000000
#> 1092 1998:1:POL:BAL:P20:03Mar:13 54.5833 19.3167 Gadus morhua 2.0000000
#> 1093 1998:1:POL:BAL:P20:03Mar:14 54.6333 19.3000 Gadus morhua 2.0000000
#> 1094 1998:1:POL:BAL:P20:03Mar:32 54.9500 18.6333 Gadus morhua 2.0000000
#> 1095 1998:1:SWE:ARG:FOT:191:3 55.8218 15.4220 Gadus morhua 2.0000000
#> 1096 1998:1:SWE:ARG:FOT:230:31 57.3755 19.1868 Gadus morhua 2.0000000
#> 1097 1998:1:RUS:ATLD:HAK:NA:35 55.5167 19.8833 Gadus morhua 3.0000000
#> 1098 2004:4:DEN:DAN2:TVL:67:32 54.8095 14.9836 Gadus morhua 2.0000000
#> 1099 2003:1:RUS:ATL:TVL:NA:2 54.5667 19.6333 Gadus morhua 2.0000000
#> 1100 2003:1:RUS:ATL:TVL:NA:29 55.5500 19.4833 Gadus morhua 2.0000000
#> 1101 2003:4:SWE:ARG:TVL:733:23 56.2532 17.8847 Gadus morhua 2.0000000
#> 1102 2003:4:SWE:ARG:TVL:737:27 55.7900 17.6892 Gadus morhua 3.0000000
#> 1103 2003:4:RUS:ATLD:TVL:NA:64 54.9200 19.5683 Gadus morhua 2.0000000
#> 1104 1999:1:DEN:DAN2:GRT:50:23 55.9050 17.7383 Gadus morhua 1.0169492
#> 1105 1999:1:GFR:SOL:H20:82:139 55.2500 17.3167 Gadus morhua 2.0000000
#> 1106 1999:1:LAT:AA36:LBT:000001:16 56.9833 20.4500 Gadus morhua 1.0000000
#> 1107 1999:4:SWE:ARG:FOT:663:27 56.2300 18.4400 Gadus morhua 2.0000000
#> 1108 2002:4:DEN:DAN2:TVL:13:6 55.4338 17.4729 Gadus morhua 2.0000000
#> 1109 2002:4:SWE:ARG:TVL:577:15 55.8770 17.6553 Gadus morhua 4.2900000
#> 1110 2002:4:SWE:ARG:TVL:574:12 56.1235 17.6527 Gadus morhua 2.0000000
#> 1111 2005:1:DEN:DAN2:TVL:108:10 55.0759 16.4263 Gadus morhua 2.0000000
#> 1112 2005:4:RUS:ATLD:TVL:36:32 55.4500 19.0767 Gadus morhua 2.0000000
#> 1113 2009:1:DEN:DAN2:TVL:120:4 55.3148 15.3390 Gadus morhua 2.0000000
#> 1114 2009:1:SWE:ARG:TVL:271:54 55.6973 14.3653 Gadus morhua 2.0000000
#> 1115 2009:1:POL:BAL:TVL:26182:30 55.0483 18.3350 Gadus morhua 2.0000000
#> 1116 1992:1:GFR:SOL:CHP:2501:47 55.6333 15.1000 Gadus morhua 1.0000000
#> 1117 1992:1:GFR:SOL:CHP:2509:22 55.6833 16.0667 Gadus morhua 1.0000000
#> 1118 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 1119 1992:1:SWE:ARG:FOT:71:22 57.8083 18.1183 Gadus morhua 1.0000000
#> 1120 1994:1:SWE:ARG:FOT:55:4 57.4733 17.5583 Gadus morhua 2.0000000
#> 1121 1994:1:SWE:ARG:FOT:70:19 57.2017 20.5700 Gadus morhua 2.0000000
#> 1122 1991:1:DEN:DAN2:GRT:153:70 55.6333 15.7833 Gadus morhua 1.0000000
#> 1123 1991:1:DEN:DAN2:GRT:55:35 57.1000 18.8667 Gadus morhua 1.0000000
#> 1124 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 2.0000000
#> 1125 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 2.0000000
#> 1126 1991:1:DEN:DAN2:GRT:80:43 56.3333 19.6000 Gadus morhua 1.0000000
#> 1127 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 1128 1991:1:LAT:90MX:LBT:000001:11 56.1167 20.5167 Gadus morhua 2.0000000
#> 1129 1991:1:GFR:SOL:CHP:26073:50 55.2500 18.3500 Gadus morhua 1.0000000
#> 1130 1991:1:LAT:90MX:LBT:000003:1 57.1500 20.6500 Gadus morhua 4.0000000
#> 1131 1991:1:LAT:90MX:LBT:000003:6 54.5500 15.3667 Gadus morhua 1.0000000
#> 1132 1991:1:POL:AA36:P20:01Jan:3 54.4333 19.0167 Gadus morhua 2.0000000
#> 1133 1991:1:LAT:90MX:LBT:000003:28 57.1833 20.6500 Gadus morhua 1.0000000
#> 1134 1991:1:POL:AA36:P20:03Mar:19 54.8000 18.9500 Gadus morhua 2.0000000
#> 1135 2000:1:DEN:DAN2:GRT:28:14 56.1310 17.7313 Gadus morhua 1.0000000
#> 1136 2000:1:DEN:DAN2:GRT:80:39 55.4108 17.4532 Gadus morhua 1.0000000
#> 1137 2000:1:POL:BAL:P20:NA:31 54.4667 19.0833 Gadus morhua 2.0000000
#> 1138 2000:1:SWE:ARG:GOV:240:37 55.9350 17.0617 Gadus morhua 2.0000000
#> 1139 2000:4:DEN:DAN2:TVL:87:44 55.4463 18.5817 Gadus morhua 2.0000000
#> 1140 2011:1:DEN:DAN2:TVL:113:4 55.2371 17.2685 Gadus morhua 2.0000000
#> 1141 2011:1:POL:BAL:TVL:25046:18 54.5550 15.4100 Gadus morhua 2.0000000
#> 1142 1995:1:DEN:DAN2:GRT:53:21 56.1666 19.5666 Gadus morhua 1.0000000
#> 1143 1995:1:LAT:RUEK:DT:000001:19 56.5167 20.1667 Gadus morhua 1.0000000
#> 1144 1995:1:RUS:RUEK:DT:NA:33 55.5167 19.0167 Gadus morhua 1.0000000
#> 1145 1995:1:SWE:ARG:GOV:80:28 57.0617 18.8750 Gadus morhua 2.0000000
#> 1146 1995:1:SWE:ARG:GOV:66:14 55.5733 18.3700 Gadus morhua 2.0000000
#> 1147 1996:1:DEN:DAN2:GRT:31:17 56.4000 18.6066 Gadus morhua 1.0000000
#> 1148 1996:1:GFR:SOL:H20:38:25 54.8500 14.0167 Gadus morhua 2.0000000
#> 1149 1996:1:GFR:SOL:H20:43:35 54.9833 13.3333 Gadus morhua 2.0000000
#> 1150 1996:1:DEN:DAN2:GRT:57:31 56.1383 19.1900 Gadus morhua 2.0000000
#> 1151 1996:1:RUS:RUEK:DT:NA:40 55.6000 19.4333 Gadus morhua 2.0000000
#> 1152 1996:1:RUS:RUEK:DT:NA:17 55.7000 18.5500 Gadus morhua 3.0000000
#> 1153 1996:1:POL:BAL:P20:01Jan:32 54.8500 18.6833 Gadus morhua 2.0000000
#> 1154 1996:4:SWE:ARG:FOT:227:22 55.8033 19.0100 Gadus morhua 2.0000000
#> 1155 2008:1:GFR:SOL2:TVS:24002:19 54.4173 12.3202 Gadus morhua 2.0000000
#> 1156 2008:1:GFR:SOL2:TVS:24183:49 54.9608 13.6165 Gadus morhua 2.0000000
#> 1157 2008:1:DEN:DAN2:TVL:56:42 55.4676 17.4168 Gadus morhua 1.9354839
#> 1158 2008:1:RUS:ATLD:TVL:49:7 55.0933 19.8833 Gadus morhua 2.0000000
#> 1159 2008:4:GFR:SOL2:TVS:24321:24 55.2015 13.3817 Gadus morhua 2.0689655
#> 1160 2008:4:RUS:ATLD:TVL:51:28 55.1583 20.0267 Gadus morhua 4.0000000
#> 1161 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 5.0000000
#> 1162 2010:1:DEN:DAN2:TVL:209:22 55.3946 17.7679 Gadus morhua 2.0000000
#> 1163 2010:1:DEN:DAN2:TVL:45:39 55.0349 15.2867 Gadus morhua 4.0000000
#> 1164 2010:1:POL:BAL:TVL:26087:33 54.8850 18.8750 Gadus morhua 4.0000000
#> 1165 2006:1:DEN:DAN2:TVL:83:45 55.6230 16.6863 Gadus morhua 2.0000000
#> 1166 2006:1:SWE:ARG:TVL:240:46 55.7543 15.8097 Gadus morhua 2.0000000
#> 1167 2007:1:DEN:DAN2:TVL:24:12 55.4725 17.8141 Gadus morhua 4.1379310
#> 1168 2007:1:POL:BAL:TVL:26044:3 55.3025 18.2847 Gadus morhua 2.0000000
#> 1169 2007:4:DEN:DAN2:TVL:3:44 55.2781 15.2228 Gadus morhua 2.0000000
#> 1170 1997:1:POL:BAL:P20:01Jan:13 54.5667 19.3667 Gadus morhua 2.0000000
#> 1171 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 1.0000000
#> 1172 1997:4:SWE:ARG:FOT:746:17 56.1283 17.5800 Gadus morhua 2.0000000
#> 1173 1997:4:SWE:ARG:FOT:745:16 56.0683 17.7583 Gadus morhua 1.7600000
#> 1174 1993:1:DEN:DAN2:GRT:11:6 55.0500 13.3833 Gadus morhua 1.0000000
#> 1175 1993:1:DEN:DAN2:GRT:162:72 54.8500 15.6667 Gadus morhua 1.0000000
#> 1176 1993:1:DEN:DAN2:GRT:117:56 56.2167 19.5000 Gadus morhua 1.0000000
#> 1177 1993:1:GFR:SOL:H20:40:12 54.9167 13.6167 Gadus morhua 2.0000000
#> 1178 1993:1:GFR:SOL:H20:49:23 55.0000 14.2333 Gadus morhua 2.0000000
#> 1179 1993:1:GFR:SOL:H20:83:37 55.1333 16.0500 Gadus morhua 2.0000000
#> 1180 1993:1:SWE:ARG:GOV:85:37 54.9983 13.9913 Gadus morhua 1.0000000
#> 1181 1993:1:SWE:ARG:FOT:55:7 55.8667 17.0855 Gadus morhua 1.0000000
#> 1182 1993:1:SWE:ARG:FOT:59:11 56.4450 16.9745 Gadus morhua 1.0000000
#> 1183 1993:1:SWE:ARG:FOT:67:19 57.7555 18.3128 Gadus morhua 1.0000000
#> 1184 2012:4:DEN:DAN2:TVL:46:14 55.3352 17.4209 Gadus morhua 2.0000000
#> 1185 2001:1:RUS:ATL:TVL:NA:8 55.0833 19.8500 Gadus morhua 2.0000000
#> 1186 2001:1:SWE:ARG:TVL:248:39 57.4478 16.9972 Gadus morhua 2.0000000
#> 1187 2001:4:DEN:DAN2:TVL:62:30 55.3911 17.7598 Gadus morhua 2.0000000
#> 1188 2001:4:DEN:DAN2:TVL:20:10 55.0959 16.3818 Gadus morhua 1.8181818
#> 1189 2013:1:DEN:DAN2:TVL:109:2 55.0912 16.3854 Gadus morhua 1.9354839
#> 1190 2013:4:GFR:SOL2:TVS:24059:40 54.8122 12.3565 Gadus morhua 2.0000000
#> 1191 2004:1:SWE:ARG:TVL:228:2 56.1137 17.7748 Gadus morhua 2.0000000
#> 1192 2004:1:RUS:ATL:TVL:NA:13 54.8333 19.6667 Gadus morhua 2.0000000
#> 1193 2004:4:DEN:DAN2:TVL:30:12 55.5016 18.5480 Gadus morhua 1.9354839
#> 1194 2004:4:DEN:DAN2:TVL:59:27 55.3409 16.2909 Gadus morhua 2.0000000
#> 1195 2004:4:RUS:ATL:TVL:NA:60 55.0633 19.8967 Gadus morhua 2.0000000
#> 1196 1998:1:DEN:DAN2:GRT:136:64 55.4800 18.4683 Gadus morhua 2.0000000
#> 1197 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 1198 1998:1:DEN:DAN2:GRT:128:60 55.7583 19.4767 Gadus morhua 1.0169492
#> 1199 1998:1:POL:BAL:P20:03Mar:14 54.6333 19.3000 Gadus morhua 2.0000000
#> 1200 1998:1:POL:BAL:P20:01Jan:5 54.6667 18.8167 Gadus morhua 2.0000000
#> 1201 1998:1:POL:BAL:P20:03Mar:63 55.3167 17.3833 Gadus morhua 2.0000000
#> 1202 1998:1:POL:BAL:P20:01Jan:46 55.3833 17.2000 Gadus morhua 2.0000000
#> 1203 1998:1:RUS:ATLD:HAK:NA:28 55.2500 19.7667 Gadus morhua 2.0000000
#> 1204 1998:1:RUS:ATLD:HAK:NA:27 55.2667 19.9500 Gadus morhua 2.0000000
#> 1205 1998:4:SWE:ARG:FOT:725:26 57.2548 20.7433 Gadus morhua 2.0000000
#> 1206 2005:1:SWE:ARG:TVL:233:41 55.7977 15.9143 Gadus morhua 2.0000000
#> 1207 2005:4:RUS:ATLD:TVL:36:35 55.1000 20.1417 Gadus morhua 2.0000000
#> 1208 2003:1:GFR:SOL:TVS:24036:24 55.0657 13.5983 Gadus morhua 2.0000000
#> 1209 2003:1:DEN:DAN2:TVL:49:26 55.1329 16.0354 Gadus morhua 2.0000000
#> 1210 2003:1:DEN:DAN2:TVL:33:17 55.2677 16.8824 Gadus morhua 2.0000000
#> 1211 2003:1:RUS:ATL:TVL:NA:2 54.5667 19.6333 Gadus morhua 2.0000000
#> 1212 2003:4:DEN:DAN2:TVL:26:12 55.3198 17.2971 Gadus morhua 2.0000000
#> 1213 2003:4:RUS:ATLD:TVL:NA:54 55.5883 19.7050 Gadus morhua 2.0000000
#> 1214 2003:4:POL:BAL:TVL:NA:3 54.4167 19.3167 Gadus morhua 2.0000000
#> 1215 1999:1:DEN:DAN2:GRT:8:5 55.8650 16.3583 Gadus morhua 1.0000000
#> 1216 1999:4:SWE:ARG:FOT:663:27 56.2300 18.4400 Gadus morhua 2.0000000
#> 1217 2002:1:GFR:SOL:TVS:479:179 54.8667 13.2833 Gadus morhua 2.0000000
#> 1218 2002:1:RUS:RUS6:TVL:NA:13 54.9333 19.4033 Gadus morhua 2.0000000
#> 1219 2002:4:DEN:DAN2:TVL:45:22 55.4607 16.4353 Gadus morhua 2.0000000
#> 1220 2002:4:SWE:ARG:TVL:574:12 56.1235 17.6527 Gadus morhua 2.0000000
#> 1221 2009:4:DEN:DAN2:TVL:107:1 55.5367 17.5367 Gadus morhua 2.0000000
#> 1222 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 3.8709677
#> 1223 2009:4:GFR:SOL2:TVS:24288:55 55.2505 14.0052 Gadus morhua 2.0000000
#> 1224 2009:4:SWE:ARG:TVL:741:29 55.6998 14.3625 Gadus morhua 2.0000000
#> 1225 2009:4:POL:BAL:TVL:NA:4 54.4333 19.3083 Gadus morhua 2.0000000
#> 1226 2009:4:POL:BAL:TVL:25453:24 54.8950 17.9250 Gadus morhua 2.0000000
#> 1227 2009:4:POL:BAL:TVL:NA:27 54.4200 19.0333 Gadus morhua 2.0000000
#> 1228 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 1229 1994:1:SWE:ARG:FOT:65:14 56.0233 18.9167 Gadus morhua 2.0000000
#> 1230 1994:1:POL:BAL:P20:Mar:37 55.2667 17.0667 Gadus morhua 2.0000000
#> 1231 1994:1:SWE:ARG:FOT:70:19 57.2017 20.5700 Gadus morhua 2.0000000
#> 1232 1994:4:GFR:SOL:H20:28:49 54.6833 14.1167 Gadus morhua 2.0000000
#> 1233 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 1234 1992:1:DEN:DAN2:GRT:64:46 57.0500 18.8667 Gadus morhua 1.0000000
#> 1235 1992:1:DEN:DAN2:GRT:82:57 55.2667 16.0500 Gadus morhua 1.0000000
#> 1236 1992:1:DEN:DAN2:GRT:11:8 54.5667 15.3000 Gadus morhua 1.0000000
#> 1237 1992:1:DEN:DAN2:GRT:78:54 55.4667 18.3000 Gadus morhua 1.0000000
#> 1238 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 1239 1991:1:DEN:DAN2:GRT:49:31 56.8500 18.8500 Gadus morhua 1.0000000
#> 1240 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 2.0000000
#> 1241 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 3.0000000
#> 1242 1991:1:DEN:DAN2:GRT:69:37 56.4333 19.9500 Gadus morhua 1.0000000
#> 1243 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 1244 1991:1:GFR:SOL:CHP:2512:38 55.8667 16.7167 Gadus morhua 1.0000000
#> 1245 1991:1:GFR:SOL:CHP:2602:43 56.1667 18.5167 Gadus morhua 1.0000000
#> 1246 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 1247 1991:1:GFR:SOL:CHP:26062:47 55.4667 18.7500 Gadus morhua 1.0000000
#> 1248 1991:1:POL:AA36:P20:01Jan:1 54.5000 19.0333 Gadus morhua 2.0000000
#> 1249 1991:1:POL:AA36:P20:03Mar:19 54.8000 18.9500 Gadus morhua 2.0000000
#> 1250 1991:1:LAT:90MX:LBT:000003:15 55.0667 19.3500 Gadus morhua 2.0000000
#> 1251 2011:1:DEN:DAN2:TVL:111:3 55.3287 17.3945 Gadus morhua 2.0000000
#> 1252 2011:1:RUS:ATLD:TVL:56:24 55.0067 19.6783 Gadus morhua 2.0000000
#> 1253 2011:1:RUS:ATLD:TVL:56:20 55.7367 17.9683 Gadus morhua 2.0000000
#> 1254 2011:4:DEN:DAN2:TVL:24:30 55.6498 14.6522 Gadus morhua 2.0000000
#> 1255 2011:4:POL:BAL:TVL:25010:13 54.4583 16.1000 Gadus morhua 2.0000000
#> 1256 2000:1:DEN:DAN2:GRT:14:7 55.7967 15.2515 Gadus morhua 0.9677419
#> 1257 2000:1:SWE:ARG:GOV:243:40 55.8617 17.6767 Gadus morhua 2.0000000
#> 1258 2000:4:SWE:ARG:GOV:567:1 55.6783 14.4700 Gadus morhua 2.0000000
#> 1259 2008:1:GFR:SOL2:TVS:24058:53 54.7433 12.3177 Gadus morhua 2.0000000
#> 1260 2008:1:GFR:SOL2:TVS:24210:48 55.0290 13.3480 Gadus morhua 2.0000000
#> 1261 2008:1:GFR:SOL2:TVS:24286:30 54.6958 14.6360 Gadus morhua 2.0000000
#> 1262 2008:1:DEN:DAN2:TVL:8:47 55.3822 15.2754 Gadus morhua 2.0000000
#> 1263 2008:1:RUS:ATLD:TVL:49:2 55.1867 20.0333 Gadus morhua 6.0000000
#> 1264 2008:1:LAT:BALL:TVL:1:27 56.2717 19.6533 Gadus morhua 2.0000000
#> 1265 2008:4:DEN:DAN2:TVL:155:10 55.3473 17.1282 Gadus morhua 2.0000000
#> 1266 2008:4:POL:BAL:TVL:26034:22 54.4983 19.2567 Gadus morhua 2.0000000
#> 1267 2008:4:POL:BAL:TVL:26037:2 54.8850 18.6667 Gadus morhua 4.0000000
#> 1268 1995:1:GFR:SOL:H20:22:14 54.5167 14.2833 Gadus morhua 2.0000000
#> 1269 1995:1:RUS:RUEK:DT:NA:14 54.9833 19.5333 Gadus morhua 2.0000000
#> 1270 1995:1:POL:BAL:P20:02Feb:90 55.3833 17.1000 Gadus morhua 1.0000000
#> 1271 1995:1:SWE:ARG:GOV:56:4 55.4583 14.7150 Gadus morhua 2.0000000
#> 1272 1995:4:SWE:ARG:FOT:257:12 57.3613 19.1700 Gadus morhua 4.0000000
#> 1273 1995:4:SWE:ARG:FOT:250:5 55.5745 18.3732 Gadus morhua 2.0000000
#> 1274 2010:1:DEN:DAN2:TVL:74:44 54.7761 15.2950 Gadus morhua 2.0000000
#> 1275 2010:1:DEN:DAN2:TVL:175:14 55.6652 14.9610 Gadus morhua 2.0000000
#> 1276 2010:1:DEN:DAN2:TVL:210:23 55.5054 18.0824 Gadus morhua 2.0000000
#> 1277 2010:1:DEN:DAN2:TVL:227:28 55.7350 17.9475 Gadus morhua 1.9354839
#> 1278 2010:1:RUS:ATL:TVL:60:10 55.6767 18.0283 Gadus morhua 3.0000000
#> 1279 2010:1:POL:BAL:TVL:26211:1 54.5000 19.3200 Gadus morhua 2.0000000
#> 1280 2010:4:DEN:DAN2:TVL:78:48 55.2576 17.4246 Gadus morhua 1.9354839
#> 1281 2010:4:DEN:DAN2:TVL:118:5 54.8186 15.9098 Gadus morhua 1.9354839
#> 1282 2010:4:SWE:ARG:TVL:672:4 55.6266 14.7594 Gadus morhua 2.0000000
#> 1283 1996:1:DEN:DAN2:GRT:61:33 55.8233 19.5483 Gadus morhua 1.0000000
#> 1284 1996:1:DEN:DAN2:GRT:14:7 54.9283 15.6983 Gadus morhua 1.0000000
#> 1285 1996:1:GFR:SOL:H20:41:31 54.8667 13.2833 Gadus morhua 2.0000000
#> 1286 1996:1:GFR:SOL:H20:68:87 54.6333 15.6333 Gadus morhua 2.0000000
#> 1287 1996:1:DEN:DAN2:GRT:30:16 56.3000 18.5516 Gadus morhua 1.0000000
#> 1288 1996:1:RUS:RUEK:DT:NA:8 54.9167 19.5333 Gadus morhua 2.0000000
#> 1289 1996:1:RUS:RUEK:DT:NA:13 55.0833 18.4333 Gadus morhua 2.0000000
#> 1290 1996:1:LAT:RUEK:DT:000001:86 55.8833 19.0333 Gadus morhua 3.0000000
#> 1291 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 2.0000000
#> 1292 1996:1:SWE:ARG:FOT:61:10 55.0833 15.5150 Gadus morhua 2.0000000
#> 1293 1996:1:SWE:ARG:FOT:69:18 55.9767 15.4200 Gadus morhua 2.0000000
#> 1294 1996:4:SWE:ARG:FOT:229:24 56.2267 18.4433 Gadus morhua 2.0000000
#> 1295 1996:4:SWE:ARG:GOV:234:29 57.4817 17.0633 Gadus morhua 2.0000000
#> 1296 2006:1:DEN:DAN2:TVL:46:25 55.0338 16.3414 Gadus morhua 2.0000000
#> 1297 2006:4:POL:BAL:TVL:25173:13 54.6522 15.5856 Gadus morhua 2.0000000
#> 1298 2006:4:POL:BAL:TVL:NA:29 55.2347 17.7672 Gadus morhua 2.0000000
#> 1299 2006:4:DEN:DAN2:TVL:7:32 54.9951 15.3587 Gadus morhua 1.9354839
#> 1300 2007:1:DEN:DAN2:TVL:108:5 54.8868 15.1407 Gadus morhua 2.0000000
#> 1301 2007:1:DEN:DAN2:TVL:12:6 55.3207 17.2498 Gadus morhua 2.0000000
#> 1302 2007:1:RUS:ATL:TVL:52:3 54.8267 19.6617 Gadus morhua 2.0000000
#> 1303 2007:1:RUS:ATL:TVL:52:14 55.1967 20.1917 Gadus morhua 2.0000000
#> 1304 2007:1:POL:BAL:TVL:26015:34 54.4353 19.2503 Gadus morhua 2.0000000
#> 1305 2007:4:POL:BAL:TVL:25212:15 55.0350 16.2856 Gadus morhua 2.0000000
#> 1306 2007:4:POL:BAL:TVL:25177:29 54.7672 15.3167 Gadus morhua 2.0000000
#> 1307 1997:1:POL:BAL:P20:01Jan:13 54.5667 19.3667 Gadus morhua 4.0000000
#> 1308 1997:1:DEN:DAN2:GRT:20:8 55.8967 17.0700 Gadus morhua 1.0000000
#> 1309 1997:1:SWE:ARG:FOT:198:20 56.0600 17.7583 Gadus morhua 2.0000000
#> 1310 1997:1:SWE:ARG:FOT:216:32 57.0533 18.9317 Gadus morhua 2.0000000
#> 1311 1997:1:SWE:ARG:FOT:224:40 57.4483 17.5350 Gadus morhua 2.0000000
#> 1312 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 1.0000000
#> 1313 1997:4:SWE:ARG:FOT:738:9 55.2983 16.0267 Gadus morhua 2.0000000
#> 1314 1997:4:LAT:AA36:LBT:2:11 56.2833 19.5833 Gadus morhua 1.0000000
#> 1315 2012:4:DEN:DAN2:TVL:42:12 55.2600 17.4149 Gadus morhua 2.0000000
#> 1316 2001:1:DEN:DAN2:TVL:34:17 55.5162 17.8679 Gadus morhua 2.0000000
#> 1317 2001:1:RUS:ATL:TVL:NA:36 55.5167 20.0167 Gadus morhua 2.0000000
#> 1318 2001:4:DEN:DAN2:TVL:73:34 55.2167 18.1222 Gadus morhua 2.0689655
#> 1319 1993:1:DEN:DAN2:GRT:159:69 54.9000 15.8500 Gadus morhua 1.0000000
#> 1320 1993:1:GFR:SOL:H20:40:12 54.9167 13.6167 Gadus morhua 2.0000000
#> 1321 1993:1:GFR:SOL:H20:51:19 55.0833 13.8167 Gadus morhua 2.0000000
#> 1322 1993:1:DEN:DAN2:GRT:79:37 56.4333 18.7167 Gadus morhua 1.0000000
#> 1323 1993:1:SWE:ARG:GOV:53:5 55.6187 16.6110 Gadus morhua 1.0000000
#> 1324 2004:4:RUS:ATL:TVL:NA:62 55.4733 20.0567 Gadus morhua 2.0000000
#> 1325 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 1326 1998:1:DEN:DAN2:GRT:128:60 55.7583 19.4767 Gadus morhua 1.0169492
#> 1327 1998:1:DEN:DAN2:GRT:114:53 56.3983 20.1000 Gadus morhua 1.0000000
#> 1328 1998:1:POL:BAL:P20:03Mar:14 54.6333 19.3000 Gadus morhua 2.0000000
#> 1329 1998:1:POL:BAL:P20:01Jan:22 54.8833 18.7000 Gadus morhua 2.0000000
#> 1330 1998:1:POL:BAL:P20:03Mar:63 55.3167 17.3833 Gadus morhua 4.0000000
#> 1331 1998:1:SWE:ARG:FOT:249:45 55.8697 16.0267 Gadus morhua 2.0000000
#> 1332 1998:1:SWE:ARG:FOT:205:13 56.0820 17.7808 Gadus morhua 2.0000000
#> 1333 1998:1:SWE:ARG:FOT:204:12 56.1390 17.5647 Gadus morhua 2.0000000
#> 1334 1998:1:RUS:ATLD:HAK:NA:33 55.6167 19.6500 Gadus morhua 2.0000000
#> 1335 2005:1:POL:BAL:TVL:33:33 55.1417 18.1300 Gadus morhua 2.0000000
#> 1336 2005:1:RUS:ATL:TVL:NA:49 55.8667 18.8000 Gadus morhua 3.0000000
#> 1337 2003:1:DEN:DAN2:TVL:42:22 55.2535 17.4952 Gadus morhua 2.0000000
#> 1338 2003:1:DEN:DAN2:TVL:77:39 55.4620 15.0234 Gadus morhua 2.0000000
#> 1339 2009:1:DEN:DAN2:TVL:179:15 54.8195 15.9679 Gadus morhua 2.0000000
#> 1340 2009:1:DEN:DAN2:TVL:116:2 55.0325 15.6637 Gadus morhua 2.0000000
#> 1341 2009:1:GFR:SOL2:TVS:24150:33 54.6383 14.7655 Gadus morhua 2.0000000
#> 1342 2009:1:RUS:ATL:TVL:57:17 55.0767 19.6133 Gadus morhua 3.0000000
#> 1343 2009:4:GFR:SOL2:TVS:24125:56 55.2608 13.9538 Gadus morhua 2.0000000
#> 1344 2009:4:DEN:DAN2:TVL:133:7 55.3369 17.4244 Gadus morhua 2.0000000
#> 1345 2009:4:GFR:SOL2:TVS:24263:34 55.2703 13.7358 Gadus morhua 2.0000000
#> 1346 2002:1:DEN:DAN2:TVL:109:43 55.8357 17.8309 Gadus morhua 2.0000000
#> 1347 2002:1:POL:BAL:TVL:7:7 54.6333 18.8500 Gadus morhua 2.0000000
#> 1348 2002:1:SWE:ARG:TVL:180:5 55.8886 17.1483 Gadus morhua 2.0000000
#> 1349 1999:1:DEN:DAN2:GRT:26:13 55.8000 15.2650 Gadus morhua 1.0000000
#> 1350 1999:1:DEN:DAN2:GRT:52:24 55.9533 17.5817 Gadus morhua 1.0000000
#> 1351 1999:1:SWE:ARG:FOT:201:10 55.6717 16.4633 Gadus morhua 2.0000000
#> 1352 1999:1:POL:BAL:P20:03Mar:55 55.4000 17.5000 Gadus morhua 2.0000000
#> 1353 1999:1:LAT:AA36:LBT:000001:16 56.9833 20.4500 Gadus morhua 1.0000000
#> 1354 1999:1:SWE:ARG:FOT:207:15 55.4583 14.7200 Gadus morhua 2.0000000
#> 1355 1999:4:SWE:ARG:FOT:671:33 55.8150 15.3950 Gadus morhua 4.0000000
#> 1356 1999:4:SWE:ARG:FOT:664:28 56.4650 18.6783 Gadus morhua 2.0000000
#> 1357 1994:1:GFR:SOL:H20:83:56 55.1333 16.0500 Gadus morhua 2.0000000
#> 1358 1994:1:DEN:DAN2:GRT:1:1 55.1000 12.8000 Gadus morhua 1.0000000
#> 1359 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 1360 1994:1:SWE:ARG:FOT:60:9 55.8383 17.6967 Gadus morhua 2.0000000
#> 1361 1994:1:SWE:ARG:FOT:58:7 57.0450 17.9483 Gadus morhua 2.0000000
#> 1362 1994:1:SWE:ARG:FOT:55:4 57.4733 17.5583 Gadus morhua 2.0000000
#> 1363 1992:1:DEN:DAN2:GRT:56:40 56.4500 18.6667 Gadus morhua 1.0000000
#> 1364 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 1365 1992:1:GFR:SOL:CHP:2810:36 56.6000 20.5833 Gadus morhua 1.0000000
#> 1366 1992:1:DEN:DAN2:GRT:85:59 55.2000 15.8833 Gadus morhua 1.0000000
#> 1367 1992:1:DEN:DAN2:GRT:83:58 55.2500 15.9667 Gadus morhua 1.0000000
#> 1368 1991:1:DEN:DAN2:GRT:15:12 54.7500 15.2833 Gadus morhua 1.0000000
#> 1369 1991:1:DEN:DAN2:GRT:45:29 56.3667 18.6500 Gadus morhua 1.0000000
#> 1370 1991:1:DEN:DAN2:GRT:49:31 56.8500 18.8500 Gadus morhua 1.0000000
#> 1371 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 1.0000000
#> 1372 1991:1:DEN:DAN2:GRT:75:40 56.5333 19.9500 Gadus morhua 1.0000000
#> 1373 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 1374 1991:1:GFR:SOL:CHP:2507:34 55.4333 15.7500 Gadus morhua 1.0000000
#> 1375 1991:1:GFR:SOL:CHP:25132:40 56.1167 17.6500 Gadus morhua 1.0000000
#> 1376 1991:1:GFR:SOL:CHP:25151:51 55.2500 17.5500 Gadus morhua 1.0000000
#> 1377 1991:1:GFR:SOL:CHP:2517:55 55.3167 16.3167 Gadus morhua 1.0000000
#> 1378 1991:1:LAT:90MX:LBT:000001:17 55.0333 19.5667 Gadus morhua 2.0000000
#> 1379 1991:1:POL:AA36:P20:01Jan:35 54.8667 18.6500 Gadus morhua 2.0000000
#> 1380 2011:1:DEN:DAN2:TVL:66:49 55.0873 16.3847 Gadus morhua 2.0000000
#> 1381 2011:1:DEN:DAN2:TVL:151:13 55.1079 15.2699 Gadus morhua 1.9354839
#> 1382 2011:4:POL:BAL:TVL:25051:16 54.6600 15.9067 Gadus morhua 2.0000000
#> 1383 2000:1:SWE:ARG:GOV:251:45 57.4717 17.5550 Gadus morhua 2.0000000
#> 1384 2000:1:SWE:ARG:GOV:238:35 55.8233 15.4367 Gadus morhua 2.0000000
#> 1385 2000:4:DEN:DAN2:TVL:87:44 55.4463 18.5817 Gadus morhua 2.0000000
#> 1386 2008:1:DEN:DAN2:TVL:189:24 55.4834 14.7154 Gadus morhua 2.0000000
#> 1387 2008:1:DEN:DAN2:TVL:2:27 55.0454 15.2606 Gadus morhua 2.0000000
#> 1388 2008:4:LTU:DAR:TVS:26057:5 55.7200 19.9600 Gadus morhua 1.0000000
#> 1389 2008:4:DEN:DAN2:TVL:155:10 55.3473 17.1282 Gadus morhua 2.0000000
#> 1390 2008:4:POL:BAL:TVL:26183:1 54.8600 18.6167 Gadus morhua 4.0000000
#> 1391 2008:4:POL:BAL:TVL:26020:18 54.9450 18.7100 Gadus morhua 4.0000000
#> 1392 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 1393 2008:4:SWE:ARG:TVL:730:32 55.6975 14.3718 Gadus morhua 2.0000000
#> 1394 2010:1:DEN:DAN2:TVL:173:13 55.6681 14.7081 Gadus morhua 2.0000000
#> 1395 2010:1:DEN:DAN2:TVL:207:20 55.2584 17.4180 Gadus morhua 4.0000000
#> 1396 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 1397 2010:1:GFR:SOL2:TVS:24104:22 55.0662 13.3385 Gadus morhua 2.0000000
#> 1398 2010:1:RUS:ATL:TVL:60:16 55.4683 18.3800 Gadus morhua 3.0000000
#> 1399 2010:1:RUS:ATL:TVL:60:18 55.3725 18.5483 Gadus morhua 2.0000000
#> 1400 2010:1:RUS:ATL:TVL:60:34 55.4750 20.0600 Gadus morhua 6.0000000
#> 1401 2010:4:DEN:DAN2:TVL:221:29 55.7825 16.0011 Gadus morhua 2.0000000
#> 1402 2010:4:RUS:ATLD:TVL:55:6 54.9383 19.4033 Gadus morhua 3.0000000
#> 1403 2010:4:SWE:ARG:TVL:673:5 55.7103 14.7189 Gadus morhua 2.0000000
#> 1404 2006:1:DEN:DAN2:TVL:30:16 55.3191 17.2908 Gadus morhua 2.0000000
#> 1405 2006:4:POL:BAL:TVL:NA:27 55.2339 17.3019 Gadus morhua 2.0000000
#> 1406 2006:4:POL:BAL:TVL:25180:16 54.8000 15.7025 Gadus morhua 2.0000000
#> 1407 2007:1:DEN:DAN2:TVL:24:12 55.4725 17.8141 Gadus morhua 2.0689655
#> 1408 2007:1:RUS:ATL:TVL:52:3 54.8267 19.6617 Gadus morhua 4.0000000
#> 1409 2007:1:POL:BAL:TVL:25394:29 54.6508 15.1681 Gadus morhua 2.0000000
#> 1410 2007:4:GFR:SOL2:TVS:24210:26 55.0115 13.3083 Gadus morhua 2.0000000
#> 1411 2007:4:POL:BAL:TVL:25453:10 54.9003 17.9511 Gadus morhua 2.0000000
#> 1412 2019:4:GFR:SOL2:TVS:24171:50 54.9370 13.0720 Gadus morhua 2.0000000
#> 1413 1995:1:DEN:DAN2:GRT:33:14 56.4166 18.7166 Gadus morhua 2.0000000
#> 1414 1995:1:LAT:RUEK:DT:000001:10 57.2833 20.6167 Gadus morhua 2.0000000
#> 1415 1995:1:SWE:ARG:GOV:92:40 57.7717 18.1667 Gadus morhua 2.0000000
#> 1416 1995:1:RUS:RUEK:DT:NA:1 55.5333 19.0833 Gadus morhua 2.0000000
#> 1417 1995:1:RUS:RUEK:DT:NA:12 55.1833 19.2000 Gadus morhua 2.0000000
#> 1418 1995:4:SWE:ARG:FOT:265:20 55.8520 17.6920 Gadus morhua 2.0000000
#> 1419 1995:4:SWE:ARG:FOT:252:7 56.2238 18.4445 Gadus morhua 2.0000000
#> 1420 1995:4:GFR:SOL:H20:26:46 54.7000 13.2333 Gadus morhua 3.0000000
#> 1421 1995:4:SWE:ARG:FOT:254:9 57.0598 18.8707 Gadus morhua 2.0000000
#> 1422 1995:4:SWE:ARG:FOT:246:1 55.9737 15.4127 Gadus morhua 2.0000000
#> 1423 1995:4:SWE:ARG:FOT:261:16 57.4853 17.0582 Gadus morhua 2.0000000
#> 1424 1995:4:SWE:ARG:FOT:250:5 55.5745 18.3732 Gadus morhua 2.0000000
#> 1425 1996:1:GFR:SOL:H20:28:23 54.6833 14.0833 Gadus morhua 2.0000000
#> 1426 1996:1:GFR:SOL:H20:32:7 54.7333 13.3333 Gadus morhua 9.0000000
#> 1427 1996:1:GFR:SOL:H20:34:11 54.7000 13.6167 Gadus morhua 2.0000000
#> 1428 1996:1:RUS:RUEK:DT:NA:18 55.6167 18.3667 Gadus morhua 2.0000000
#> 1429 1996:1:SWE:ARG:FOT:93:42 57.3400 17.8867 Gadus morhua 2.0000000
#> 1430 1996:1:SWE:ARG:FOT:95:44 57.4800 17.5533 Gadus morhua 2.0000000
#> 1431 1996:1:SWE:ARG:FOT:90:39 57.0483 18.9283 Gadus morhua 2.0000000
#> 1432 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 4.0000000
#> 1433 1996:4:SWE:ARG:GOV:234:29 57.4817 17.0633 Gadus morhua 2.0000000
#> 1434 1996:4:SWE:ARG:FOT:216:11 55.5900 14.6267 Gadus morhua 2.4000000
#> 1435 2016:4:GFR:SOL2:TVS:24016:18 54.6915 12.9722 Gadus morhua 2.0000000
#> 1436 1997:1:POL:BAL:P20:01Jan:13 54.5667 19.3667 Gadus morhua 2.0000000
#> 1437 1997:1:POL:BAL:P20:01Jan:20 54.8500 18.6833 Gadus morhua 2.0000000
#> 1438 1997:1:POL:BAL:P20:03Mar:18 54.7333 19.3000 Gadus morhua 2.0000000
#> 1439 1997:4:SWE:ARG:FOT:743:14 55.9367 17.0533 Gadus morhua 2.0000000
#> 1440 1997:4:SWE:ARG:FOT:768:35 57.3698 16.9115 Gadus morhua 2.0000000
#> 1441 2001:1:GFR:SOL:TVS:662:41 54.7167 13.7167 Gadus morhua 2.0000000
#> 1442 2001:1:SWE:ARG:TVL:247:38 57.4623 17.0925 Gadus morhua 2.1400000
#> 1443 2001:1:RUS:ATL:TVL:NA:56 56.6333 20.4667 Gadus morhua 3.0000000
#> 1444 2001:1:SWE:ARG:TVL:204:1 55.4808 14.6013 Gadus morhua 2.0000000
#> 1445 2001:4:SWE:ARG:TVL:610:18 56.1105 17.7665 Gadus morhua 2.0000000
#> 1446 2001:4:SWE:ARG:TVL:624:27 55.8145 15.3912 Gadus morhua 2.0000000
#> 1447 2001:4:SWE:ARG:TVL:627:29 55.6940 16.6640 Gadus morhua 2.0000000
#> 1448 1993:1:DEN:DAN2:GRT:41:19 55.5667 16.1833 Gadus morhua 1.0000000
#> 1449 2004:4:DEN:DAN2:TVL:28:11 55.3672 18.5559 Gadus morhua 2.0000000
#> 1450 2004:4:RUS:ATL:TVL:NA:66 54.9217 19.5700 Gadus morhua 2.0000000
#> 1451 2005:1:DEN:DAN2:TVL:51:42 55.4501 14.4631 Gadus morhua 2.0000000
#> 1452 2005:1:GFR:SOL2:TVS:24286:44 54.7160 14.6533 Gadus morhua 1.9354839
#> 1453 2005:1:RUS:ATL:TVL:NA:52 55.3333 18.7667 Gadus morhua 2.0000000
#> 1454 2005:4:SWE:ARG:TVL:612:13 56.5413 16.8375 Gadus morhua 2.0000000
#> 1455 2005:4:RUS:ATLD:TVL:36:32 55.4500 19.0767 Gadus morhua 2.0000000
#> 1456 2005:4:POL:BAL:TVL:NA:13 54.5675 15.6850 Gadus morhua 2.0000000
#> 1457 1998:1:GFR:SOL:H20:66:69 56.1000 17.6333 Gadus morhua 2.0000000
#> 1458 1998:1:DEN:DAN2:GRT:128:60 55.7583 19.4767 Gadus morhua 1.0169492
#> 1459 1998:1:DEN:DAN2:GRT:118:55 56.4150 19.9200 Gadus morhua 1.0000000
#> 1460 1998:1:POL:BAL:P20:01Jan:17 54.9000 18.7333 Gadus morhua 2.0000000
#> 1461 1998:1:SWE:ARG:FOT:231:32 57.1642 18.8173 Gadus morhua 2.0000000
#> 1462 1998:1:RUS:ATLD:HAK:NA:37 55.5167 20.0333 Gadus morhua 2.0000000
#> 1463 1998:4:SWE:ARG:FOT:703:9 55.5833 16.4317 Gadus morhua 2.0000000
#> 1464 1998:4:GFR:SOL:H20:29:68 54.5833 14.1500 Gadus morhua 2.0000000
#> 1465 2009:1:GFR:SOL2:TVS:24283:37 54.9000 14.2133 Gadus morhua 2.7272727
#> 1466 2009:1:DEN:DAN2:TVL:116:2 55.0325 15.6637 Gadus morhua 2.0000000
#> 1467 2009:1:RUS:ATL:TVL:57:15 55.3867 19.9483 Gadus morhua 2.0000000
#> 1468 2009:4:DEN:DAN2:TVL:111:3 55.6217 18.0790 Gadus morhua 2.0000000
#> 1469 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 1.9354839
#> 1470 2009:4:DEN:DAN2:TVL:137:9 55.4022 17.4111 Gadus morhua 2.0000000
#> 1471 2009:4:DEN:DAN2:TVL:199:17 55.0098 16.2973 Gadus morhua 2.0689655
#> 1472 2003:1:DEN:DAN2:TVL:86:44 55.4843 16.4220 Gadus morhua 2.0000000
#> 1473 2003:4:DEN:DAN2:TVL:49:24 55.4697 15.5539 Gadus morhua 1.9354839
#> 1474 2003:4:RUS:ATLD:TVL:NA:57 55.1033 20.0700 Gadus morhua 2.0000000
#> 1475 2002:1:POL:BAL:TVL:20:20 55.4500 18.3833 Gadus morhua 2.0000000
#> 1476 1999:1:DEN:DAN2:GRT:2:2 55.1183 12.8517 Gadus morhua 1.0000000
#> 1477 1999:1:DEN:DAN2:GRT:99:46 55.3883 18.1300 Gadus morhua 1.0169492
#> 1478 1994:1:DEN:DAN2:GRT:2:2 55.1333 12.7833 Gadus morhua 1.0000000
#> 1479 1994:1:SWE:ARG:FOT:56:5 57.3677 17.9097 Gadus morhua 2.0000000
#> 1480 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 1.0000000
#> 1481 1994:1:SWE:ARG:GOV:83:32 55.4567 14.7050 Gadus morhua 2.0000000
#> 1482 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 1483 1992:1:GFR:SOL:CHP:2516:18 55.3167 16.3333 Gadus morhua 1.0000000
#> 1484 1992:1:DEN:DAN2:GRT:61:44 56.8500 18.8833 Gadus morhua 1.0000000
#> 1485 1992:1:GFR:SOL:CHP:26011:28 56.1333 18.3000 Gadus morhua 1.0000000
#> 1486 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 4.0000000
#> 1487 1992:1:GFR:SOL:CHP:2810:36 56.6000 20.5833 Gadus morhua 1.0000000
#> 1488 1992:1:SWE:ARG:GOV:87:38 55.7983 15.8866 Gadus morhua 1.0000000
#> 1489 1992:1:SWE:ARG:FOT:71:22 57.8083 18.1183 Gadus morhua 2.0000000
#> 1490 1992:1:SWE:ARG:GOV:88:39 55.8767 16.0650 Gadus morhua 1.0000000
#> 1491 1992:1:SWE:ARG:GOV:58:9 55.4517 14.6483 Gadus morhua 2.0000000
#> 1492 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 1493 2011:1:DEN:DAN2:TVL:87:54 55.3761 16.9989 Gadus morhua 1.9354839
#> 1494 2011:1:GFR:SOL2:TVS:24324:48 55.1502 14.1498 Gadus morhua 2.0000000
#> 1495 2011:1:POL:BAL:TVL:26182:32 55.0450 18.3300 Gadus morhua 3.0000000
#> 1496 2011:1:POL:BAL:TVL:25173:19 54.6533 15.5683 Gadus morhua 2.0000000
#> 1497 2011:4:DEN:DAN2:TVL:175:16 55.0536 16.2955 Gadus morhua 2.0000000
#> 1498 2014:4:DEN:DAN2:TVL:74:14 55.4310 18.9252 Gadus morhua 2.0000000
#> 1499 2008:1:GFR:SOL2:TVS:24306:25 54.7107 13.8147 Gadus morhua 2.0000000
#> 1500 2008:1:GFR:SOL2:TVS:24316:41 55.1505 14.0718 Gadus morhua 2.0000000
#> 1501 2008:1:DEN:DAN2:TVL:30:35 55.3465 17.1142 Gadus morhua 2.0000000
#> 1502 2008:1:POL:BAL:TVL:25061:15 54.8117 16.0217 Gadus morhua 2.0000000
#> 1503 2008:1:SWE:ARG:TVL:243:48 55.7869 16.6369 Gadus morhua 4.0000000
#> 1504 2008:4:POL:BAL:TVL:26132:24 54.5400 18.8867 Gadus morhua 2.0000000
#> 1505 2008:4:POL:BAL:TVL:26182:14 55.0433 18.3083 Gadus morhua 2.0000000
#> 1506 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 1507 1991:1:DEN:DAN2:GRT:36:24 56.2500 17.9167 Gadus morhua 1.0000000
#> 1508 1991:1:DEN:DAN2:GRT:50:32 56.9667 18.8000 Gadus morhua 1.0000000
#> 1509 1991:1:DEN:DAN2:GRT:71:39 56.4833 20.2167 Gadus morhua 1.0000000
#> 1510 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 2.0000000
#> 1511 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 4.0000000
#> 1512 1991:1:GFR:SOL:CHP:2604:44 56.1833 18.9333 Gadus morhua 1.0000000
#> 1513 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 1514 1991:1:LAT:90MX:LBT:000003:19 55.1000 19.4000 Gadus morhua 2.0000000
#> 1515 1991:1:LAT:90MX:LBT:000003:21 55.1167 19.4000 Gadus morhua 2.0000000
#> 1516 1991:1:POL:AA36:P20:01Jan:3 54.4333 19.0167 Gadus morhua 2.0000000
#> 1517 2000:4:SWE:ARG:GOV:589:23 55.9550 15.3717 Gadus morhua 2.0000000
#> 1518 2010:1:DEN:DAN2:TVL:100:1 55.0897 16.3814 Gadus morhua 2.0000000
#> 1519 2010:1:DEN:DAN2:TVL:74:44 54.7761 15.2950 Gadus morhua 2.0000000
#> 1520 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 1521 2010:1:DEN:DAN2:TVL:214:25 55.3212 18.7542 Gadus morhua 2.0000000
#> 1522 2010:1:DEN:DAN2:TVL:45:39 55.0349 15.2867 Gadus morhua 2.0000000
#> 1523 2010:1:RUS:ATL:TVL:60:18 55.3725 18.5483 Gadus morhua 2.0000000
#> 1524 2010:1:POL:BAL:TVL:26087:33 54.8850 18.8750 Gadus morhua 4.0000000
#> 1525 2010:1:LAT:BALL:TVL:1:30 55.7017 19.9733 Gadus morhua 40.0000000
#> 1526 2010:4:DEN:DAN2:TVL:78:48 55.2576 17.4246 Gadus morhua 1.9354839
#> 1527 2010:4:DEN:DAN2:TVL:118:5 54.8186 15.9098 Gadus morhua 1.9354839
#> 1528 2010:4:DEN:DAN2:TVL:57:45 55.3877 17.1156 Gadus morhua 2.0000000
#> 1529 2010:4:DEN:DAN2:TVL:166:16 54.6558 15.0806 Gadus morhua 2.0000000
#> 1530 2010:4:DEN:DAN2:TVL:108:3 55.7400 16.7201 Gadus morhua 1.9354839
#> 1531 2010:4:RUS:ATLD:TVL:55:17 55.1067 19.7017 Gadus morhua 2.0000000
#> 1532 2006:4:GFR:SOL2:TVS:24147:21 55.3053 13.8498 Gadus morhua 2.0000000
#> 1533 2006:4:POL:BAL:TVL:NA:26 55.3503 17.1500 Gadus morhua 2.0000000
#> 1534 2007:1:DEN:DAN2:TVL:60:32 55.2964 14.3607 Gadus morhua 2.0000000
#> 1535 2007:1:GFR:SOL2:TVS:24012:26 54.5403 14.2080 Gadus morhua 2.0000000
#> 1536 2007:1:RUS:ATL:TVL:52:1 55.0733 19.8833 Gadus morhua 2.0000000
#> 1537 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 2.0000000
#> 1538 2007:4:DEN:DAN2:TVL:3:44 55.2781 15.2228 Gadus morhua 2.0000000
#> 1539 2007:4:SWE:ARG:TVL:697:22 55.7140 14.4279 Gadus morhua 2.0000000
#> 1540 1996:1:DEN:DAN2:GRT:32:18 56.4650 18.7033 Gadus morhua 1.0000000
#> 1541 1996:1:DEN:DAN2:GRT:46:26 56.4433 19.9866 Gadus morhua 1.0000000
#> 1542 1996:1:GFR:SOL:H20:27:131 54.5167 13.7833 Gadus morhua 2.0000000
#> 1543 1996:1:DEN:DAN2:GRT:45:25 56.3700 20.0666 Gadus morhua 1.0000000
#> 1544 1996:1:DEN:DAN2:GRT:57:31 56.1383 19.1900 Gadus morhua 1.0000000
#> 1545 1996:1:RUS:RUEK:DT:NA:18 55.6167 18.3667 Gadus morhua 2.0000000
#> 1546 1996:1:RUS:RUEK:DT:NA:16 55.1500 18.7667 Gadus morhua 2.0000000
#> 1547 1996:1:RUS:RUEK:DT:NA:26 55.0500 19.7333 Gadus morhua 2.0000000
#> 1548 1996:1:SWE:ARG:FOT:95:44 57.4800 17.5533 Gadus morhua 2.0000000
#> 1549 1996:1:POL:BAL:P20:03Mar:18 54.7333 19.2500 Gadus morhua 2.0000000
#> 1550 1996:1:SWE:ARG:FOT:57:6 55.2100 13.2283 Gadus morhua 2.0000000
#> 1551 1996:4:SWE:ARG:FOT:224:19 55.8733 17.6500 Gadus morhua 2.0000000
#> 1552 1996:4:SWE:ARG:GOV:235:30 57.4700 17.5483 Gadus morhua 2.0000000
#> 1553 1995:1:DEN:DAN2:GRT:8:2 55.3833 16.7000 Gadus morhua 1.0169492
#> 1554 1995:1:GFR:SOL:H20:45:45 55.0667 13.7500 Gadus morhua 9.0000000
#> 1555 1995:1:DEN:DAN2:GRT:38:16 56.8666 18.8500 Gadus morhua 1.0000000
#> 1556 1995:1:DEN:DAN2:GRT:40:17 56.9833 18.7833 Gadus morhua 1.0000000
#> 1557 1995:1:LAT:RUEK:DT:000001:19 56.5167 20.1667 Gadus morhua 1.0000000
#> 1558 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 2.0000000
#> 1559 1995:1:SWE:ARG:GOV:75:23 56.0783 17.7750 Gadus morhua 2.0000000
#> 1560 1995:1:SWE:ARG:GOV:98:46 55.0000 13.9767 Gadus morhua 2.0000000
#> 1561 2012:1:DEN:DAN2:TVL:89:52 55.2325 15.9539 Gadus morhua 2.0000000
#> 1562 2012:1:DEN:DAN2:TVL:91:53 55.2792 16.0086 Gadus morhua 2.0000000
#> 1563 2012:4:POL:BAL:TVL:26217:37 54.5167 18.8683 Gadus morhua 10.0000000
#> 1564 1997:1:DEN:DAN2:GRT:51:24 56.5317 20.2483 Gadus morhua 1.0000000
#> 1565 1997:1:DEN:DAN2:GRT:46:21 56.2600 19.6833 Gadus morhua 1.0000000
#> 1566 1997:1:POL:BAL:P20:02Feb:4 54.4667 19.0667 Gadus morhua 2.0000000
#> 1567 1997:1:POL:BAL:P20:03Mar:16 54.5667 19.3667 Gadus morhua 2.0000000
#> 1568 1997:1:SWE:ARG:FOT:214:30 57.8400 19.5283 Gadus morhua 2.0000000
#> 1569 1997:1:SWE:ARG:FOT:224:40 57.4483 17.5350 Gadus morhua 2.0000000
#> 1570 1997:1:SWE:ARG:FOT:194:16 55.8517 17.6900 Gadus morhua 2.0000000
#> 1571 1997:1:SWE:ARG:FOT:196:18 55.8700 16.0367 Gadus morhua 2.0000000
#> 1572 1997:4:LAT:AA36:LBT:2:20 56.0667 19.4833 Gadus morhua 1.0000000
#> 1573 2013:1:DEN:DAN2:TVL:162:17 55.6239 14.7369 Gadus morhua 2.0000000
#> 1574 2013:1:POL:BAL:TVL:25054:15 54.7267 15.7717 Gadus morhua 6.0000000
#> 1575 2001:1:GFR:SOL:TVS:3337:81 54.3667 12.1833 Gadus morhua 2.0000000
#> 1576 2001:1:DEN:DAN2:TVL:84:41 55.1334 15.2926 Gadus morhua 2.0000000
#> 1577 2001:1:POL:BAL:TVL:21:21 54.7833 18.6833 Gadus morhua 2.0000000
#> 1578 2001:1:POL:BAL:TVL:35:35 54.4333 19.2833 Gadus morhua 2.0000000
#> 1579 2001:4:SWE:ARG:TVL:610:18 56.1105 17.7665 Gadus morhua 2.0000000
#> 1580 2001:4:SWE:ARG:TVL:602:12 56.7075 16.9898 Gadus morhua 2.0000000
#> 1581 2004:1:DEN:DAN2:TVL:22:8 55.5430 17.9137 Gadus morhua 4.0000000
#> 1582 2004:1:DEN:DAN2:TVL:70:34 55.8392 17.6615 Gadus morhua 2.0000000
#> 1583 2004:1:LAT:AA36:TVS:1:7 55.7500 20.0500 Gadus morhua 2.0000000
#> 1584 2004:1:POL:BAL:TVL:32:32 54.8500 15.6833 Gadus morhua 2.0000000
#> 1585 2004:1:SWE:ARG:TVL:260:30 55.8652 16.6122 Gadus morhua 2.0000000
#> 1586 2004:4:DEN:DAN2:TVL:54:25 55.8723 16.4272 Gadus morhua 2.0000000
#> 1587 2005:1:RUS:ATL:TVL:NA:11 54.6000 19.5833 Gadus morhua 2.0000000
#> 1588 2005:1:RUS:ATL:TVL:NA:23 55.3667 19.9333 Gadus morhua 2.0000000
#> 1589 2005:4:POL:BAL:TVL:NA:15 54.6355 15.6025 Gadus morhua 4.0000000
#> 1590 1993:1:GFR:SOL:H20:43:15 54.9833 13.3167 Gadus morhua 2.0000000
#> 1591 1993:1:GFR:SOL:H20:50:17 55.0500 13.6167 Gadus morhua 2.0000000
#> 1592 1993:1:SWE:ARG:FOT:57:9 55.8015 17.7367 Gadus morhua 1.0000000
#> 1593 1993:1:SWE:ARG:FOT:79:31 55.3282 16.0507 Gadus morhua 1.0000000
#> 1594 1993:1:SWE:ARG:FOT:80:32 55.4120 15.3205 Gadus morhua 1.0000000
#> 1595 1993:4:GFR:SOL:H20:29:45 54.5833 14.1333 Gadus morhua 4.0000000
#> 1596 2009:1:DEN:DAN2:TVL:120:4 55.3148 15.3390 Gadus morhua 4.0000000
#> 1597 2009:1:POL:BAL:TVL:25056:16 54.7567 15.9450 Gadus morhua 2.0000000
#> 1598 2009:1:DEN:DAN2:TVL:142:8 54.8385 15.4049 Gadus morhua 2.0000000
#> 1599 2009:1:RUS:ATL:TVL:57:3 55.0933 19.8850 Gadus morhua 2.0000000
#> 1600 2009:1:RUS:ATL:TVL:57:8 55.1967 20.1933 Gadus morhua 8.0000000
#> 1601 2009:1:RUS:ATL:TVL:57:9 55.3450 20.6850 Gadus morhua 2.0000000
#> 1602 2009:1:RUS:ATL:TVL:57:20 56.0417 18.9450 Gadus morhua 2.0000000
#> 1603 2009:1:POL:BAL:TVL:26137:28 55.7133 18.6300 Gadus morhua 4.0000000
#> 1604 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 1.9354839
#> 1605 2009:4:SWE:ARG:TVL:737:25 55.6926 14.8758 Gadus morhua 2.0000000
#> 1606 2009:4:POL:BAL:TVL:26186:2 54.4067 19.2733 Gadus morhua 2.0000000
#> 1607 1998:1:DEN:DAN2:GRT:122:57 55.9783 19.4350 Gadus morhua 1.1764706
#> 1608 1998:1:DEN:DAN2:GRT:44:21 56.0583 17.5983 Gadus morhua 1.0000000
#> 1609 1998:1:DEN:DAN2:GRT:114:53 56.3983 20.1000 Gadus morhua 1.0000000
#> 1610 1998:1:POL:BAL:P20:01Jan:8 54.7000 18.8333 Gadus morhua 2.0000000
#> 1611 1998:1:SWE:ARG:FOT:228:29 57.8751 19.5121 Gadus morhua 2.0000000
#> 1612 1998:1:RUS:ATLD:HAK:NA:27 55.2667 19.9500 Gadus morhua 2.0000000
#> 1613 1998:4:SWE:ARG:FOT:703:9 55.5833 16.4317 Gadus morhua 2.0000000
#> 1614 1998:4:SWE:ARG:FOT:704:10 55.6767 16.5217 Gadus morhua 2.0000000
#> 1615 1998:4:SWE:ARG:FOT:720:22 56.0548 17.7505 Gadus morhua 2.0000000
#> 1616 1998:4:SWE:ARG:FOT:725:26 57.2548 20.7433 Gadus morhua 2.0000000
#> 1617 2003:1:DEN:DAN2:TVL:77:39 55.4620 15.0234 Gadus morhua 2.0000000
#> 1618 2003:1:SWE:ARG:TVL:227:8 55.8190 15.2603 Gadus morhua 2.0000000
#> 1619 2003:1:SWE:ARG:TVL:228:9 55.7705 15.2563 Gadus morhua 2.0000000
#> 1620 2003:4:DEN:DAN2:TVL:32:15 55.6290 16.2536 Gadus morhua 2.0000000
#> 1621 2003:4:DEN:DAN2:TVL:45:22 55.0450 16.9995 Gadus morhua 2.0000000
#> 1622 2003:4:RUS:ATLD:TVL:NA:56 55.0933 19.8633 Gadus morhua 2.0000000
#> 1623 2002:1:RUS:RUS6:TVL:NA:32 55.4733 20.0517 Gadus morhua 4.0000000
#> 1624 2002:1:SWE:ARG:TVL:186:11 55.6951 14.4148 Gadus morhua 2.0000000
#> 1625 2002:4:DEN:DAN2:TVL:45:22 55.4607 16.4353 Gadus morhua 2.0000000
#> 1626 1999:1:RUS:ATL:HAK:NA:5 54.9500 19.6333 Gadus morhua 2.0000000
#> 1627 1999:4:SWE:ARG:FOT:671:33 55.8150 15.3950 Gadus morhua 2.0000000
#> 1628 1994:1:DEN:DAN2:GRT:46:23 56.3667 19.4833 Gadus morhua 1.0000000
#> 1629 1994:1:SWE:ARG:GOV:83:32 55.4567 14.7050 Gadus morhua 2.0000000
#> 1630 1994:4:SWE:ARG:FOT:269:14 55.8500 17.6933 Gadus morhua 2.0000000
#> 1631 1994:4:SWE:ARG:FOT:273:18 57.4550 17.5417 Gadus morhua 2.0000000
#> 1632 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 4.0000000
#> 1633 1994:4:SWE:ARG:FOT:264:9 55.4617 14.5000 Gadus morhua 2.0000000
#> 1634 2011:1:DEN:DAN2:TVL:113:4 55.2371 17.2685 Gadus morhua 2.0000000
#> 1635 2011:1:DEN:DAN2:TVL:232:30 55.4494 15.1457 Gadus morhua 4.8000000
#> 1636 2011:1:RUS:ATLD:TVL:56:23 55.3717 18.5508 Gadus morhua 4.0000000
#> 1637 2011:1:POL:BAL:TVL:26191:4 54.6817 19.2683 Gadus morhua 5.0000000
#> 1638 1992:1:DEN:DAN2:GRT:54:38 56.2833 18.5500 Gadus morhua 1.0000000
#> 1639 1992:1:GFR:SOL:CHP:2503:15 55.2500 15.0833 Gadus morhua 1.0000000
#> 1640 1992:1:GFR:SOL:CHP:25081:21 55.5833 15.8833 Gadus morhua 1.0000000
#> 1641 1992:1:DEN:DAN2:GRT:18:13 54.8000 15.4667 Gadus morhua 1.0000000
#> 1642 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 1.0000000
#> 1643 1992:1:GFR:SOL:CHP:28111:37 56.6000 20.5833 Gadus morhua 1.0000000
#> 1644 1992:1:GFR:SOL:H20:25:31 54.7167 13.1333 Gadus morhua 2.0000000
#> 1645 1992:1:DEN:DAN2:GRT:85:59 55.2000 15.8833 Gadus morhua 2.0000000
#> 1646 1992:1:SWE:ARG:GOV:85:36 55.6783 16.5233 Gadus morhua 1.0000000
#> 1647 1992:1:SWE:ARG:FOT:71:22 57.8083 18.1183 Gadus morhua 1.0000000
#> 1648 2008:1:DEN:DAN2:TVL:130:7 54.7780 15.6704 Gadus morhua 2.0000000
#> 1649 2008:1:DEN:DAN2:TVL:28:34 55.3729 16.9913 Gadus morhua 1.9354839
#> 1650 2008:1:DEN:DAN2:TVL:2:27 55.0454 15.2606 Gadus morhua 2.0000000
#> 1651 2008:1:DEN:DAN2:TVL:81:48 55.5946 16.6646 Gadus morhua 2.0000000
#> 1652 2008:1:SWE:ARG:TVL:249:54 55.6989 14.3623 Gadus morhua 2.0000000
#> 1653 2008:1:SWE:ARG:TVL:243:48 55.7869 16.6369 Gadus morhua 2.0000000
#> 1654 2008:4:POL:BAL:TVL:26168:19 54.6667 18.8250 Gadus morhua 2.0000000
#> 1655 2008:4:LAT:BALL:TVL:2:26 55.8033 20.0700 Gadus morhua 4.0000000
#> 1656 2008:4:RUS:ATLD:TVL:51:26 54.8267 19.6633 Gadus morhua 2.0000000
#> 1657 2006:1:RUS:ATLD:TVL:NA:20 55.6033 19.0450 Gadus morhua 2.0000000
#> 1658 2006:1:POL:BAL:TVL:25175:17 54.6683 15.6342 Gadus morhua 2.0000000
#> 1659 2006:4:DEN:DAN2:TVL:33:12 55.3175 14.9461 Gadus morhua 2.0000000
#> 1660 2006:4:DEN:DAN2:TVL:38:15 55.7902 15.2362 Gadus morhua 2.0689655
#> 1661 2010:1:DEN:DAN2:TVL:74:44 54.7761 15.2950 Gadus morhua 2.0000000
#> 1662 2010:1:DEN:DAN2:TVL:173:13 55.6681 14.7081 Gadus morhua 2.0000000
#> 1663 2010:1:DEN:DAN2:TVL:210:23 55.5054 18.0824 Gadus morhua 2.0000000
#> 1664 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 4.0000000
#> 1665 2010:1:DEN:DAN2:TVL:214:25 55.3212 18.7542 Gadus morhua 2.0000000
#> 1666 2010:1:RUS:ATL:TVL:60:18 55.3725 18.5483 Gadus morhua 2.0000000
#> 1667 2010:1:RUS:ATL:TVL:60:23 54.9217 19.5692 Gadus morhua 16.0000000
#> 1668 2010:4:DEN:DAN2:TVL:118:5 54.8186 15.9098 Gadus morhua 5.8064516
#> 1669 2010:4:DEN:DAN2:TVL:172:19 54.9556 15.5273 Gadus morhua 2.0000000
#> 1670 2007:1:DEN:DAN2:TVL:67:35 55.0082 16.2977 Gadus morhua 4.0000000
#> 1671 2007:1:DEN:DAN2:TVL:36:18 55.6084 18.3701 Gadus morhua 2.0000000
#> 1672 2007:1:SWE:ARG:TVL:185:1 55.8673 16.4273 Gadus morhua 2.0000000
#> 1673 2007:1:RUS:ATL:TVL:52:3 54.8267 19.6617 Gadus morhua 2.0000000
#> 1674 2007:1:RUS:ATL:TVL:52:14 55.1967 20.1917 Gadus morhua 12.0000000
#> 1675 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 6.0000000
#> 1676 2007:4:SWE:ARG:TVL:697:22 55.7140 14.4279 Gadus morhua 2.0000000
#> 1677 2007:4:POL:BAL:TVL:25453:10 54.9003 17.9511 Gadus morhua 2.0000000
#> 1678 2000:1:GFR:SOL:H20:41:44 54.8667 13.3167 Gadus morhua 2.0000000
#> 1679 2000:1:DEN:DAN2:GRT:160:81 55.9417 17.2320 Gadus morhua 2.0689655
#> 1680 2000:1:DEN:DAN2:GRT:30:15 55.9085 17.7397 Gadus morhua 1.0000000
#> 1681 2000:1:GFR:SOL:H20:42:47 54.9000 13.1333 Gadus morhua 2.0000000
#> 1682 2000:1:RUS:ATL:HAK:NA:9 55.1167 19.6833 Gadus morhua 2.0000000
#> 1683 2000:1:POL:BAL:P20:NA:40 54.4167 19.2833 Gadus morhua 2.0000000
#> 1684 2000:4:SWE:ARG:GOV:594:27 55.9362 17.0593 Gadus morhua 2.0000000
#> 1685 2000:4:SWE:ARG:GOV:611:42 56.9323 17.1785 Gadus morhua 2.0000000
#> 1686 1991:1:DEN:DAN2:GRT:40:26 56.3833 18.6000 Gadus morhua 1.0000000
#> 1687 1991:1:DEN:DAN2:GRT:50:32 56.9667 18.8000 Gadus morhua 1.0000000
#> 1688 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 1.0000000
#> 1689 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 1.0000000
#> 1690 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 1691 1991:1:DEN:DAN2:GRT:83:46 55.6000 19.4833 Gadus morhua 1.0000000
#> 1692 1991:1:GFR:SOL:CHP:2602:43 56.1667 18.5167 Gadus morhua 1.0000000
#> 1693 1991:1:LAT:90MX:LBT:000001:11 56.1167 20.5167 Gadus morhua 2.0000000
#> 1694 1991:1:GFR:SOL:CHP:2604:44 56.1833 18.9333 Gadus morhua 1.0000000
#> 1695 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 1696 1991:1:GFR:SOL:CHP:2412:80 54.7833 13.4833 Gadus morhua 1.0000000
#> 1697 2012:1:DEN:DAN2:TVL:24:42 55.2944 14.3557 Gadus morhua 2.0000000
#> 1698 2012:1:DEN:DAN2:TVL:89:52 55.2325 15.9539 Gadus morhua 2.0000000
#> 1699 2012:4:DEN:DAN2:TVL:28:9 54.8472 16.0592 Gadus morhua 2.0000000
#> 1700 1996:1:GFR:SOL:H20:31:21 54.6167 14.2000 Gadus morhua 2.0000000
#> 1701 1996:1:DEN:DAN2:GRT:12:6 54.8700 15.5716 Gadus morhua 1.0169492
#> 1702 1996:1:GFR:SOL:H20:75:83 55.2833 15.0667 Gadus morhua 4.0000000
#> 1703 1996:1:DEN:DAN2:GRT:28:15 56.3133 18.5783 Gadus morhua 1.0000000
#> 1704 1996:1:DEN:DAN2:GRT:30:16 56.3000 18.5516 Gadus morhua 1.0000000
#> 1705 1996:1:DEN:DAN2:GRT:51:29 56.3450 19.6316 Gadus morhua 1.0000000
#> 1706 1996:1:DEN:DAN2:GRT:40:22 57.4300 19.2083 Gadus morhua 1.0000000
#> 1707 1996:1:DEN:DAN2:GRT:93:44 55.4700 15.5566 Gadus morhua 1.0000000
#> 1708 1996:1:SWE:ARG:FOT:86:35 57.8433 19.5267 Gadus morhua 2.0000000
#> 1709 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 4.0000000
#> 1710 1995:1:DEN:DAN2:GRT:59:24 56.4333 20.0333 Gadus morhua 1.0000000
#> 1711 1995:1:GFR:SOL:H20:45:45 55.0667 13.7500 Gadus morhua 9.0000000
#> 1712 1995:1:GFR:SOL:H20:71:67 55.6833 15.0333 Gadus morhua 2.0000000
#> 1713 1995:1:DEN:DAN2:GRT:40:17 56.9833 18.7833 Gadus morhua 1.0000000
#> 1714 1995:1:RUS:RUEK:DT:NA:17 54.5833 19.5667 Gadus morhua 2.0000000
#> 1715 1995:1:SWE:ARG:GOV:90:38 57.8583 19.4767 Gadus morhua 2.0000000
#> 1716 1995:1:RUS:RUEK:DT:NA:1 55.5333 19.0833 Gadus morhua 2.0000000
#> 1717 1995:1:RUS:RUEK:DT:NA:2 55.6333 19.0333 Gadus morhua 6.0000000
#> 1718 1995:4:SWE:ARG:FOT:265:20 55.8520 17.6920 Gadus morhua 2.0000000
#> 1719 1995:4:GFR:SOL:H20:25:47 54.7167 13.1333 Gadus morhua 4.0000000
#> 1720 1995:4:SWE:ARG:FOT:257:12 57.3613 19.1700 Gadus morhua 2.0000000
#> 1721 1995:4:SWE:ARG:FOT:250:5 55.5745 18.3732 Gadus morhua 4.0000000
#> 1722 1997:1:DEN:DAN2:GRT:11:4 55.1550 16.4450 Gadus morhua 1.0000000
#> 1723 1997:1:DEN:DAN2:GRT:32:14 56.4583 18.6300 Gadus morhua 0.9836066
#> 1724 1997:1:POL:BAL:P20:01Jan:15 54.7333 19.2833 Gadus morhua 2.0000000
#> 1725 1997:1:POL:BAL:P20:01Jan:14 54.6333 19.3167 Gadus morhua 2.0000000
#> 1726 1997:1:POL:BAL:P20:03Mar:17 54.6333 19.3000 Gadus morhua 2.0000000
#> 1727 1997:1:RUS:ATL:HAK:NA:36 55.6500 19.9333 Gadus morhua 2.0000000
#> 1728 1997:1:SWE:ARG:FOT:224:40 57.4483 17.5350 Gadus morhua 2.0000000
#> 1729 1997:1:SWE:ARG:FOT:197:19 55.9333 17.0500 Gadus morhua 4.0000000
#> 1730 1997:4:SWE:ARG:FOT:756:26 56.2205 18.4318 Gadus morhua 2.0000000
#> 1731 2001:1:GFR:SOL:TVS:673:66 54.9667 13.9167 Gadus morhua 2.0000000
#> 1732 2001:1:DEN:DAN2:TVL:6:3 55.0214 13.7642 Gadus morhua 2.0000000
#> 1733 2001:1:DEN:DAN2:TVL:110:46 54.8396 15.9946 Gadus morhua 2.0000000
#> 1734 2001:1:RUS:ATL:TVL:NA:51 56.4000 20.0500 Gadus morhua 2.0000000
#> 1735 2001:1:SWE:ARG:TVL:206:3 55.7067 14.4118 Gadus morhua 2.0000000
#> 1736 2001:1:SWE:ARG:TVL:209:6 55.7713 15.1722 Gadus morhua 2.0000000
#> 1737 2001:1:SWE:ARG:TVL:251:42 57.4595 17.5488 Gadus morhua 1.7100000
#> 1738 2001:4:GFR:SOL:TVS:904:47 54.9667 13.5500 Gadus morhua 2.0000000
#> 1739 2001:4:SWE:ARG:TVL:617:23 55.6590 14.5368 Gadus morhua 2.0000000
#> 1740 2005:1:SWE:ARG:TVL:233:41 55.7977 15.9143 Gadus morhua 2.0000000
#> 1741 2005:1:POL:BAL:TVL:33:33 55.1417 18.1300 Gadus morhua 2.0000000
#> 1742 2005:1:RUS:ATL:TVL:NA:9 54.8667 19.6500 Gadus morhua 2.0000000
#> 1743 2005:1:RUS:ATL:TVL:NA:5 55.1000 20.1333 Gadus morhua 2.0000000
#> 1744 2005:4:POL:BAL:TVL:NA:30 54.4508 19.2847 Gadus morhua 2.0000000
#> 1745 2004:1:DEN:DAN2:TVL:68:33 55.9110 17.7372 Gadus morhua 2.0000000
#> 1746 2004:1:RUS:ATL:TVL:NA:10 55.3667 19.9167 Gadus morhua 4.0000000
#> 1747 2004:1:RUS:ATL:TVL:NA:4 55.6333 18.9667 Gadus morhua 2.0000000
#> 1748 2004:4:DEN:DAN2:TVL:22:8 55.4644 17.4119 Gadus morhua 2.0000000
#> 1749 2004:4:LAT:AA36:TVS:2:2 55.7867 20.1600 Gadus morhua 2.0000000
#> 1750 2004:4:POL:BAL:TVL:NA:26 54.8500 16.7000 Gadus morhua 2.0000000
#> 1751 2009:1:DEN:DAN2:TVL:220:23 55.4699 17.8155 Gadus morhua 1.9354839
#> 1752 2009:1:GFR:SOL2:TVS:24089:56 54.9050 12.9128 Gadus morhua 2.0000000
#> 1753 2009:1:GFR:SOL2:TVS:24228:20 55.0105 13.6503 Gadus morhua 2.0000000
#> 1754 2009:1:DEN:DAN2:TVL:116:2 55.0325 15.6637 Gadus morhua 2.0000000
#> 1755 2009:1:GFR:SOL2:TVS:24005:50 54.6892 12.1972 Gadus morhua 2.0000000
#> 1756 2009:1:RUS:ATL:TVL:57:5 55.1000 20.1200 Gadus morhua 3.0000000
#> 1757 2009:1:RUS:ATL:TVL:57:37 55.1933 18.9450 Gadus morhua 2.0000000
#> 1758 2009:1:RUS:ATL:TVL:57:34 55.4683 18.3567 Gadus morhua 2.0000000
#> 1759 2009:1:SWE:ARG:TVL:244:31 55.8287 16.4292 Gadus morhua 2.0000000
#> 1760 2009:4:DEN:DAN2:TVL:131:6 55.2582 17.4758 Gadus morhua 1.9354839
#> 1761 2009:4:DEN:DAN2:TVL:137:9 55.4022 17.4111 Gadus morhua 4.0000000
#> 1762 2009:4:GFR:SOL2:TVS:24288:55 55.2505 14.0052 Gadus morhua 2.0000000
#> 1763 1993:1:GFR:SOL:H20:82:40 55.2500 17.5500 Gadus morhua 2.0000000
#> 1764 1993:1:DEN:DAN2:GRT:7:4 55.2167 13.2667 Gadus morhua 1.0000000
#> 1765 1993:1:DEN:DAN2:GRT:74:32 56.4000 18.6000 Gadus morhua 1.0000000
#> 1766 1993:1:SWE:ARG:FOT:63:15 57.3685 16.9133 Gadus morhua 1.0000000
#> 1767 1993:1:SWE:ARG:FOT:66:18 57.8210 18.1230 Gadus morhua 1.0000000
#> 1768 1993:4:SWE:ARG:FOT:264:33 55.8633 16.0116 Gadus morhua 6.0000000
#> 1769 2003:4:DEN:DAN2:TVL:55:27 55.5436 14.7456 Gadus morhua 2.0000000
#> 1770 1998:1:DEN:DAN2:GRT:130:61 55.6167 19.4983 Gadus morhua 1.0000000
#> 1771 1998:1:DEN:DAN2:GRT:36:17 55.8967 17.0650 Gadus morhua 1.0000000
#> 1772 1998:1:RUS:ATLD:HAK:NA:34 55.6167 19.7333 Gadus morhua 2.0000000
#> 1773 1998:1:POL:BAL:P20:01Jan:48 55.2667 17.1833 Gadus morhua 4.0000000
#> 1774 1998:1:POL:BAL:P20:03Mar:63 55.3167 17.3833 Gadus morhua 4.0000000
#> 1775 1998:1:POL:BAL:P20:03Mar:64 55.3833 17.5000 Gadus morhua 2.0000000
#> 1776 1998:1:SWE:ARG:FOT:206:14 55.8513 17.6927 Gadus morhua 2.0000000
#> 1777 1998:1:SWE:ARG:FOT:217:22 56.0140 18.9093 Gadus morhua 2.0000000
#> 1778 1998:4:SWE:ARG:FOT:692:1 55.6800 14.4733 Gadus morhua 4.0000000
#> 1779 2002:1:GFR:SOL:TVS:788:181 54.8833 12.8167 Gadus morhua 2.0000000
#> 1780 2002:1:SWE:ARG:TVL:194:19 55.9572 15.3810 Gadus morhua 2.0000000
#> 1781 2002:1:RUS:RUS6:TVL:NA:9 55.0967 19.8567 Gadus morhua 5.0000000
#> 1782 2002:4:GFR:SOL:TVS:1278:37 54.6333 15.9167 Gadus morhua 2.0000000
#> 1783 2002:4:DEN:DAN2:TVL:33:16 55.9975 19.2590 Gadus morhua 2.0000000
#> 1784 2002:4:GFR:SOL:TVS:24012:52 54.7500 13.4833 Gadus morhua 3.0000000
#> 1785 2002:4:DEN:DAN2:TVL:10:4 55.4908 14.6121 Gadus morhua 2.0000000
#> 1786 1999:1:DEN:DAN2:GRT:39:18 54.7900 15.2967 Gadus morhua 1.0000000
#> 1787 1999:1:RUS:ATL:HAK:NA:5 54.9500 19.6333 Gadus morhua 2.0000000
#> 1788 1999:1:POL:BAL:P20:02Feb:25 54.8830 15.6833 Gadus morhua 2.0000000
#> 1789 1999:1:SWE:ARG:FOT:246:52 56.3375 18.4766 Gadus morhua 2.0000000
#> 1790 1999:4:SWE:ARG:FOT:671:33 55.8150 15.3950 Gadus morhua 2.0000000
#> 1791 1999:4:LAT:AA36:LBT:2:8 56.3667 20.1333 Gadus morhua 2.0000000
#> 1792 1999:4:SWE:ARG:FOT:659:24 56.0733 17.7633 Gadus morhua 2.0000000
#> 1793 1994:1:DEN:DAN2:GRT:23:13 56.8500 18.8667 Gadus morhua 1.0000000
#> 1794 1994:1:SWE:ARG:FOT:76:25 57.0717 18.8350 Gadus morhua 2.0000000
#> 1795 1994:1:DEN:DAN2:GRT:74:39 56.1167 18.2667 Gadus morhua 2.0000000
#> 1796 1994:1:SWE:ARG:FOT:78:27 56.4717 18.6767 Gadus morhua 2.0000000
#> 1797 1994:1:SWE:ARG:FOT:60:9 55.8383 17.6967 Gadus morhua 2.0000000
#> 1798 1994:1:SWE:ARG:GOV:83:32 55.4567 14.7050 Gadus morhua 2.0000000
#> 1799 1994:1:POL:BAL:P20:Mar:8 54.6833 18.7833 Gadus morhua 2.0000000
#> 1800 1994:1:SWE:ARG:FOT:61:10 56.0533 17.7350 Gadus morhua 2.0000000
#> 1801 1994:4:SWE:ARG:FOT:273:18 57.4550 17.5417 Gadus morhua 2.0000000
#> 1802 1994:4:SWE:ARG:FOT:283:28 56.2533 18.4833 Gadus morhua 2.0000000
#> 1803 2011:1:DEN:DAN2:TVL:18:19 54.8808 15.2861 Gadus morhua 2.0689655
#> 1804 2011:1:DEN:DAN2:TVL:187:21 55.5417 16.1755 Gadus morhua 2.0000000
#> 1805 2011:1:GFR:SOL2:TVS:24182:25 54.8698 13.4062 Gadus morhua 2.0000000
#> 1806 2011:1:POL:BAL:TVL:25394:15 54.6567 15.1633 Gadus morhua 11.0000000
#> 1807 2008:1:DEN:DAN2:TVL:111:6 55.0247 16.3220 Gadus morhua 2.0000000
#> 1808 2008:1:DEN:DAN2:TVL:30:35 55.3465 17.1142 Gadus morhua 2.0000000
#> 1809 2008:1:SWE:ARG:TVL:243:48 55.7869 16.6369 Gadus morhua 2.0000000
#> 1810 2008:4:GFR:SOL2:TVS:24142:28 55.2705 14.0387 Gadus morhua 2.0000000
#> 1811 2008:4:DEN:DAN2:TVL:132:7 54.8132 14.9560 Gadus morhua 2.0000000
#> 1812 2008:4:RUS:ATLD:TVL:51:28 55.1583 20.0267 Gadus morhua 4.0000000
#> 1813 2008:4:RUS:ATLD:TVL:51:33 55.2125 20.1450 Gadus morhua 2.0000000
#> 1814 2008:4:SWE:ARG:TVL:718:24 55.6255 14.7595 Gadus morhua 6.2800000
#> 1815 2008:4:LAT:BALL:TVL:2:29 55.6417 20.1550 Gadus morhua 4.0000000
#> 1816 2008:4:RUS:ATLD:TVL:51:27 55.0067 19.6750 Gadus morhua 4.0000000
#> 1817 2008:4:RUS:ATLD:TVL:51:23 55.0933 19.8817 Gadus morhua 5.0000000
#> 1818 1992:1:DEN:DAN2:GRT:16:12 54.7667 15.2833 Gadus morhua 1.0000000
#> 1819 1992:1:DEN:DAN2:GRT:81:56 55.3167 16.1833 Gadus morhua 1.0000000
#> 1820 1992:1:DEN:DAN2:GRT:52:37 56.1167 18.2667 Gadus morhua 1.0000000
#> 1821 1992:1:DEN:DAN2:GRT:86:60 55.1667 15.7667 Gadus morhua 1.0000000
#> 1822 1992:1:DEN:DAN2:GRT:54:38 56.2833 18.5500 Gadus morhua 1.0000000
#> 1823 1992:1:DEN:DAN2:GRT:22:15 54.8500 15.6167 Gadus morhua 1.0000000
#> 1824 1992:1:GFR:SOL:CHP:2504:46 55.3167 15.3167 Gadus morhua 1.0000000
#> 1825 1992:1:GFR:SOL:CHP:2518:16 55.2500 16.0500 Gadus morhua 1.0000000
#> 1826 1992:1:GFR:SOL:CHP:26012:41 56.1833 18.3667 Gadus morhua 1.0000000
#> 1827 1992:1:GFR:SOL:CHP:26021:29 56.1500 18.5333 Gadus morhua 3.0000000
#> 1828 1992:1:DEN:DAN2:GRT:85:59 55.2000 15.8833 Gadus morhua 1.0000000
#> 1829 1992:1:SWE:ARG:GOV:56:7 55.0133 13.9233 Gadus morhua 1.0000000
#> 1830 2006:1:DEN:DAN2:TVL:2:11 55.3990 17.7860 Gadus morhua 2.0000000
#> 1831 2006:1:DEN:DAN2:TVL:49:26 54.8483 15.7272 Gadus morhua 2.0000000
#> 1832 2006:1:POL:BAL:TVL:25193:8 54.8503 15.6856 Gadus morhua 2.0000000
#> 1833 2006:4:DEN:DAN2:TVL:104:2 55.4969 14.6127 Gadus morhua 4.0000000
#> 1834 2006:4:DEN:DAN2:TVL:81:38 55.8170 17.6741 Gadus morhua 2.0000000
#> 1835 2006:4:POL:BAL:TVL:26104:3 55.3672 18.5517 Gadus morhua 2.0000000
#> 1836 2007:1:DEN:DAN2:TVL:64:34 54.8431 15.8427 Gadus morhua 1.9354839
#> 1837 2007:1:DEN:DAN2:TVL:24:12 55.4725 17.8141 Gadus morhua 2.0689655
#> 1838 2007:1:DEN:DAN2:TVL:36:18 55.6084 18.3701 Gadus morhua 2.0000000
#> 1839 2007:4:DEN:DAN2:TVL:283:41 55.2576 17.4398 Gadus morhua 2.0000000
#> 1840 2007:4:SWE:ARG:TVL:695:20 55.6526 14.6536 Gadus morhua 2.0000000
#> 1841 2010:1:DEN:DAN2:TVL:102:2 55.1465 16.0199 Gadus morhua 2.0000000
#> 1842 2010:1:DEN:DAN2:TVL:98:48 55.0102 16.2765 Gadus morhua 2.0000000
#> 1843 2010:1:DEN:DAN2:TVL:207:20 55.2584 17.4180 Gadus morhua 2.0000000
#> 1844 2010:1:DEN:DAN2:TVL:213:24 55.3701 18.4283 Gadus morhua 2.0000000
#> 1845 2010:1:RUS:ATL:TVL:60:18 55.3725 18.5483 Gadus morhua 2.0000000
#> 1846 2010:1:RUS:ATL:TVL:60:23 54.9217 19.5692 Gadus morhua 16.0000000
#> 1847 2010:4:DEN:DAN2:TVL:78:48 55.2576 17.4246 Gadus morhua 1.9354839
#> 1848 2010:4:DEN:DAN2:TVL:120:7 54.8392 16.0528 Gadus morhua 2.0000000
#> 1849 2010:4:DEN:DAN2:TVL:172:19 54.9556 15.5273 Gadus morhua 2.0000000
#> 1850 2000:1:GFR:SOL:H20:44:51 55.0333 13.4167 Gadus morhua 2.0000000
#> 1851 2000:1:SWE:ARG:GOV:243:40 55.8617 17.6767 Gadus morhua 2.0000000
#> 1852 2000:4:LAT:AA36:LBT:2:4 56.0000 19.4000 Gadus morhua 2.0000000
#> 1853 2012:1:DEN:DAN2:TVL:89:52 55.2325 15.9539 Gadus morhua 2.0000000
#> 1854 2012:1:POL:BAL:TVL:25193:36 54.8450 15.6833 Gadus morhua 2.0000000
#> 1855 2012:1:DEN:DAN2:TVL:112:2 55.1243 16.3840 Gadus morhua 2.0000000
#> 1856 2012:4:GFR:SOL2:TVS:24078:32 54.7072 14.1368 Gadus morhua 2.0000000
#> 1857 1991:1:DEN:DAN2:GRT:19:14 54.8667 15.4167 Gadus morhua 1.0000000
#> 1858 1991:1:DEN:DAN2:GRT:40:26 56.3833 18.6000 Gadus morhua 2.0000000
#> 1859 1991:1:DEN:DAN2:GRT:49:31 56.8500 18.8500 Gadus morhua 1.0000000
#> 1860 1991:1:DEN:DAN2:GRT:50:32 56.9667 18.8000 Gadus morhua 1.0000000
#> 1861 1991:1:DEN:DAN2:GRT:55:35 57.1000 18.8667 Gadus morhua 1.0000000
#> 1862 1991:1:DEN:DAN2:GRT:72:1 56.4500 19.9500 Gadus morhua 3.0000000
#> 1863 1991:1:DEN:DAN2:GRT:76:41 56.4667 19.8167 Gadus morhua 3.0000000
#> 1864 1991:1:DEN:DAN2:GRT:81:44 56.2333 19.5167 Gadus morhua 1.0000000
#> 1865 1991:1:GFR:SOL:CHP:2602:43 56.1667 18.5167 Gadus morhua 2.0000000
#> 1866 1991:1:GFR:SOL:CHP:2604:44 56.1833 18.9333 Gadus morhua 2.0000000
#> 1867 1991:1:GFR:SOL:CHP:2605:45 55.9167 18.7000 Gadus morhua 1.0000000
#> 1868 1991:1:GFR:SOL:CHP:26062:47 55.4667 18.7500 Gadus morhua 3.0000000
#> 1869 1991:1:GFR:SOL:CHP:26071:48 54.9667 18.6000 Gadus morhua 1.0000000
#> 1870 1991:1:GFR:SOL:CHP:25151:51 55.2500 17.5500 Gadus morhua 1.0000000
#> 1871 1991:1:LAT:90MX:LBT:000001:16 55.0667 19.8167 Gadus morhua 2.0000000
#> 1872 1991:1:GFR:SOL:CHP:25252:64 54.7667 14.7500 Gadus morhua 1.0000000
#> 1873 1991:1:GFR:SOL:CHP:25223:76 54.8833 15.7833 Gadus morhua 1.0000000
#> 1874 1991:1:GFR:SOL:CHP:25224:77 54.8500 15.6667 Gadus morhua 1.0000000
#> 1875 1991:1:GFR:SOL:CHP:2411:79 54.6667 13.7167 Gadus morhua 1.0000000
#> 1876 1991:1:LAT:90MX:LBT:000003:30 57.1500 20.6500 Gadus morhua 4.0000000
#> 1877 1991:1:POL:AA36:P20:01Jan:1 54.5000 19.0333 Gadus morhua 2.0000000
#> 1878 1991:1:LAT:90MX:LBT:000003:28 57.1833 20.6500 Gadus morhua 1.0000000
#> 1879 1991:1:POL:AA36:P20:03Mar:19 54.8000 18.9500 Gadus morhua 2.0000000
#> 1880 1991:1:POL:AA36:P20:03Mar:11 54.9167 18.7333 Gadus morhua 2.0000000
#> 1881 1991:1:LAT:90MX:LBT:000003:11 54.8667 15.7167 Gadus morhua 1.0000000
#> 1882 1991:1:LAT:90MX:LBT:000003:13 54.8500 15.7167 Gadus morhua 1.0000000
#> 1883 1991:1:LAT:90MX:LBT:000003:15 55.0667 19.3500 Gadus morhua 2.0000000
#> 1884 1996:1:DEN:DAN2:GRT:22:12 55.7550 16.3416 Gadus morhua 1.0000000
#> 1885 1996:1:DEN:DAN2:GRT:31:17 56.4000 18.6066 Gadus morhua 1.0000000
#> 1886 1996:1:DEN:DAN2:GRT:57:31 56.1383 19.1900 Gadus morhua 2.0000000
#> 1887 1996:1:DEN:DAN2:GRT:30:16 56.3000 18.5516 Gadus morhua 2.0000000
#> 1888 1996:1:RUS:RUEK:DT:NA:34 55.2500 19.8500 Gadus morhua 2.0000000
#> 1889 1996:1:RUS:RUEK:DT:NA:17 55.7000 18.5500 Gadus morhua 3.0000000
#> 1890 1996:1:SWE:ARG:FOT:64:13 55.2767 16.8733 Gadus morhua 2.0000000
#> 1891 1996:1:SWE:ARG:FOT:100:49 55.8517 17.6917 Gadus morhua 2.0000000
#> 1892 1996:1:SWE:ARG:FOT:52:1 55.6700 14.4867 Gadus morhua 2.0000000
#> 1893 1996:1:SWE:ARG:FOT:99:48 56.0567 17.7533 Gadus morhua 2.0000000
#> 1894 1996:1:SWE:ARG:FOT:78:27 56.0250 18.9150 Gadus morhua 2.0000000
#> 1895 1996:1:SWE:ARG:FOT:61:10 55.0833 15.5150 Gadus morhua 2.0000000
#> 1896 2013:4:DEN:DAN2:TVL:78:46 55.2587 17.4086 Gadus morhua 2.0689655
#> 1897 2013:4:DEN:DAN2:TVL:82:49 55.3138 17.3395 Gadus morhua 2.0000000
#> 1898 1995:1:DEN:DAN2:GRT:134:49 55.4833 16.1500 Gadus morhua 1.0000000
#> 1899 1995:1:GFR:SOL:H20:45:45 55.0667 13.7500 Gadus morhua 9.0000000
#> 1900 1995:1:LAT:RUEK:DT:000001:23 56.4833 20.0167 Gadus morhua 1.0000000
#> 1901 1995:1:LAT:RUEK:DT:000001:10 57.2833 20.6167 Gadus morhua 2.0000000
#> 1902 1995:1:LAT:RUEK:DT:000001:21 56.5167 20.2000 Gadus morhua 1.0000000
#> 1903 1995:1:SWE:ARG:GOV:93:41 57.4700 17.5483 Gadus morhua 2.0000000
#> 1904 1995:1:SWE:ARG:GOV:94:42 57.4767 17.0667 Gadus morhua 2.0000000
#> 1905 1995:1:RUS:RUEK:DT:NA:7 55.3667 19.1000 Gadus morhua 2.0000000
#> 1906 1995:4:SWE:ARG:FOT:266:21 55.9280 17.1058 Gadus morhua 2.0000000
#> 1907 1995:4:SWE:ARG:FOT:265:20 55.8520 17.6920 Gadus morhua 2.0000000
#> 1908 1995:4:SWE:ARG:FOT:257:12 57.3613 19.1700 Gadus morhua 4.0000000
#> 1909 1995:4:SWE:ARG:FOT:250:5 55.5745 18.3732 Gadus morhua 2.0000000
#> 1910 1997:1:DEN:DAN2:GRT:121:52 55.2050 13.3683 Gadus morhua 1.0000000
#> 1911 1997:1:GFR:SOL:H20:29:29 54.5833 14.1500 Gadus morhua 2.0000000
#> 1912 1997:1:POL:BAL:P20:01Jan:13 54.5667 19.3667 Gadus morhua 2.0000000
#> 1913 1997:1:POL:BAL:P20:03Mar:64 54.7167 16.4333 Gadus morhua 2.0000000
#> 1914 1997:1:POL:BAL:P20:03Mar:23 54.6333 18.8500 Gadus morhua 2.0000000
#> 1915 1997:1:RUS:ATL:HAK:NA:36 55.6500 19.9333 Gadus morhua 2.0000000
#> 1916 1997:1:RUS:ATL:HAK:NA:16 54.9500 19.6500 Gadus morhua 2.0000000
#> 1917 1997:1:SWE:ARG:FOT:194:16 55.8517 17.6900 Gadus morhua 2.0000000
#> 1918 1997:1:SWE:ARG:FOT:195:17 55.7983 15.9567 Gadus morhua 2.0000000
#> 1919 1997:1:SWE:ARG:FOT:197:19 55.9333 17.0500 Gadus morhua 2.0000000
#> 1920 1997:4:LAT:AA36:LBT:2:16 56.6500 20.5167 Gadus morhua 1.0000000
#> 1921 1997:4:SWE:ARG:FOT:743:14 55.9367 17.0533 Gadus morhua 2.0000000
#> 1922 1997:4:SWE:ARG:FOT:745:16 56.0683 17.7583 Gadus morhua 1.7600000
#> 1923 1997:4:SWE:ARG:FOT:754:24 55.8068 19.0093 Gadus morhua 2.0000000
#> a b length_cm length_cm2 weight_kg CPUEun_kg
#> 1 0.007345618 3.082202 335 335 445.375628 445.375628
#> 2 0.007345618 3.082202 285 285 270.617596 270.617596
#> 3 0.007345618 3.082202 225 225 130.596025 261.192050
#> 4 0.007345618 3.082202 220 220 121.856351 121.856351
#> 5 0.007345618 3.082202 215 215 113.520627 113.520627
#> 6 0.007345618 3.082202 180 180 65.649848 65.649848
#> 7 0.007345618 3.082202 175 175 60.190044 60.190044
#> 8 0.007345618 3.082202 160 160 45.663723 45.663723
#> 9 0.007345618 3.082202 150 150 37.426665 74.853330
#> 10 0.007345618 3.082202 145 145 33.713286 101.139857
#> 11 0.007345618 3.082202 140 140 30.257178 30.257178
#> 12 0.008367352 3.055881 136 136 27.696774 27.696774
#> 13 0.006985661 3.112176 127 127 24.638516 24.638516
#> 14 0.007345618 3.082202 130 130 24.078461 48.156922
#> 15 0.008339286 3.052078 127 127 21.983793 21.983793
#> 16 0.008367352 3.055881 123 123 20.374619 20.374619
#> 17 0.007345618 3.082202 121 121 19.301610 38.603220
#> 18 0.006985661 3.112176 116 116 18.585049 37.170099
#> 19 0.007444717 3.070310 121 121 18.477547 36.955094
#> 20 0.006436894 3.144784 112 112 17.907056 35.814111
#> 21 0.008339286 3.052078 118 118 17.566088 17.566088
#> 22 0.008367352 3.055881 117 117 17.487111 17.487111
#> 23 0.007554303 3.071838 118 118 17.485605 34.971211
#> 24 0.007243730 3.076256 118 118 17.123826 34.247653
#> 25 0.007345618 3.082202 116 116 16.947469 16.947469
#> 26 0.006436894 3.144784 110 110 16.920578 16.920578
#> 27 0.007243730 3.076256 117 117 16.681324 33.362649
#> 28 0.007554303 3.071838 116 116 16.591104 33.182208
#> 29 0.007554303 3.071838 115 115 16.155661 32.311321
#> 30 0.006436894 3.144784 108 108 15.971828 15.971828
#> 31 0.008367352 3.055881 113 113 15.723585 15.723585
#> 32 0.008367352 3.055881 113 113 15.723585 31.447171
#> 33 0.007303857 3.095567 111 111 15.667059 31.334117
#> 34 0.006830676 3.097913 113 113 15.657476 31.314953
#> 35 0.007345618 3.082202 113 113 15.632585 31.265169
#> 36 0.006985661 3.112176 109 109 15.312178 15.312178
#> 37 0.008367352 3.055881 112 112 15.302225 15.302225
#> 38 0.009208543 3.001584 118 118 15.244674 30.489348
#> 39 0.007303857 3.095567 110 110 15.234247 15.234247
#> 40 0.009197813 2.994628 119 119 15.106897 30.213795
#> 41 0.007017543 3.107987 109 109 15.082734 15.082734
#> 42 0.006436894 3.144784 106 106 15.060022 15.060022
#> 43 0.008339286 3.052078 112 112 14.979689 14.979689
#> 44 0.007345618 3.082202 111 111 14.795406 29.590811
#> 45 0.008339286 3.052078 111 111 14.575210 29.150421
#> 46 0.008377248 3.027632 115 115 14.525642 29.051283
#> 47 0.006985661 3.112176 107 107 14.454618 14.454618
#> 48 0.007693063 3.064660 111 111 14.266578 28.533156
#> 49 0.006436894 3.144784 104 104 14.184378 14.184378
#> 50 0.006985661 3.112176 106 106 14.038329 14.038329
#> 51 0.006985661 3.112176 106 106 14.038329 14.038329
#> 52 0.006985661 3.112176 106 106 14.038329 42.114988
#> 53 0.009197813 2.994628 116 116 13.994840 27.989680
#> 54 0.007345618 3.082202 109 109 13.989053 41.967160
#> 55 0.007345618 3.082202 109 109 13.989053 27.978107
#> 56 0.007746254 3.044723 113 113 13.808505 27.617010
#> 57 0.006436894 3.144784 103 103 13.759873 13.759873
#> 58 0.007554303 3.071838 109 109 13.703734 26.523356
#> 59 0.008367352 3.055881 108 108 13.692703 27.385406
#> 60 0.007303857 3.095567 106 106 13.583858 13.583858
#> 61 0.007920229 3.035684 113 113 13.528063 27.056126
#> 62 0.007554303 3.071838 108 108 13.321194 13.321194
#> 63 0.008367352 3.055881 107 107 13.308941 13.308941
#> 64 0.008367352 3.055881 107 107 13.308941 26.617882
#> 65 0.007991791 3.046753 110 110 13.251433 26.502865
#> 66 0.006985661 3.112176 104 104 13.230305 13.230305
#> 67 0.007345618 3.082202 107 107 13.212927 26.425854
#> 68 0.007303857 3.095567 105 105 13.191070 13.191070
#> 69 0.007920229 3.035684 112 112 13.167902 26.335805
#> 70 0.007746254 3.044723 111 111 13.077762 26.155523
#> 71 0.007017543 3.107987 104 104 13.034621 13.034621
#> 72 0.008339286 3.052078 107 107 13.030682 26.061364
#> 73 0.008339286 3.052078 107 107 13.030682 26.061364
#> 74 0.007554303 3.071838 107 107 12.945922 25.891844
#> 75 0.007991791 3.046753 109 109 12.887802 25.775603
#> 76 0.007345618 3.082202 106 106 12.836011 25.672023
#> 77 0.007303857 3.095567 104 104 12.806044 12.806044
#> 78 0.008339286 3.052078 106 106 12.662546 25.325092
#> 79 0.008367352 3.055881 105 105 12.563254 12.563254
#> 80 0.008367352 3.055881 105 105 12.563254 25.126509
#> 81 0.007917341 3.037179 110 110 12.550280 25.100560
#> 82 0.008046923 3.063870 105 105 12.539822 12.539822
#> 83 0.008046923 3.063870 105 105 12.539822 25.079643
#> 84 0.006436894 3.144784 100 100 12.538458 25.076917
#> 85 0.007920229 3.035684 110 110 12.466982 199.471718
#> 86 0.007345618 3.082202 105 105 12.466427 12.466427
#> 87 0.007303857 3.095567 103 103 12.428698 24.857396
#> 88 0.008339286 3.052078 105 105 12.301468 12.301468
#> 89 0.008339286 3.052078 105 105 12.301468 24.602936
#> 90 0.008367352 3.055881 104 104 12.201186 12.201186
#> 91 0.006830676 3.097913 104 104 12.107575 24.215150
#> 92 0.006985661 3.112176 101 101 12.078361 24.156722
#> 93 0.007693063 3.064660 105 105 12.032567 24.065133
#> 94 0.007746254 3.044723 108 108 12.031051 24.062103
#> 95 0.009208543 3.001584 109 109 12.014261 23.253408
#> 96 0.007444717 3.070310 105 105 11.954332 23.908664
#> 97 0.007017543 3.107987 101 101 11.901173 11.901173
#> 98 0.007917341 3.037179 108 108 11.869990 23.739980
#> 99 0.007917341 3.037179 108 108 11.869990 24.558600
#> 100 0.008367352 3.055881 103 103 11.846204 47.384816
#> 101 0.008367352 3.055881 103 103 11.846204 23.692408
#> 102 0.008367352 3.055881 103 103 11.846204 23.692408
#> 103 0.006436894 3.144784 98 98 11.766629 11.766629
#> 104 0.006436894 3.144784 98 98 11.766629 11.766629
#> 105 0.006830676 3.097913 103 103 11.750544 23.501088
#> 106 0.006830676 3.097913 103 103 11.750544 23.501088
#> 107 0.007345618 3.082202 103 103 11.748955 23.497909
#> 108 0.007303857 3.095567 101 101 11.696724 23.393448
#> 109 0.009208543 3.001584 108 108 11.686447 23.372893
#> 110 0.007693063 3.064660 104 104 11.684810 23.369621
#> 111 0.009197813 2.994628 109 109 11.614986 23.229971
#> 112 0.009197813 2.994628 109 109 11.614986 23.229971
#> 113 0.009197813 2.994628 109 109 11.614986 23.229971
#> 114 0.008339286 3.052078 103 103 11.600208 11.600208
#> 115 0.007017543 3.107987 100 100 11.538756 11.538756
#> 116 0.007017543 3.107987 100 100 11.538756 11.538756
#> 117 0.007554303 3.071838 103 103 11.516080 23.032159
#> 118 0.008367352 3.055881 102 102 11.498237 11.498237
#> 119 0.007345618 3.082202 102 102 11.400917 22.801833
#> 120 0.007345618 3.082202 102 102 11.400917 22.801833
#> 121 0.006830676 3.097913 102 102 11.400711 45.602846
#> 122 0.006436894 3.144784 97 97 11.393158 22.786315
#> 123 0.007746254 3.044723 106 106 11.365456 22.730911
#> 124 0.009208543 3.001584 107 107 11.364652 22.729304
#> 125 0.008339286 3.052078 102 102 11.259885 11.259885
#> 126 0.007017543 3.107987 99 99 11.183899 11.183899
#> 127 0.007017543 3.107987 99 99 11.183899 11.183899
#> 128 0.007554303 3.071838 102 102 11.176070 44.704280
#> 129 0.007554303 3.071838 102 102 11.176070 22.352140
#> 130 0.007991791 3.046753 104 104 11.169814 22.339627
#> 131 0.008367352 3.055881 101 101 11.157214 11.157214
#> 132 0.007920229 3.035684 106 106 11.141068 22.282137
#> 133 0.007920229 3.035684 106 106 11.141068 22.282137
#> 134 0.006830676 3.097913 101 101 11.058001 22.116001
#> 135 0.006830676 3.097913 101 101 11.058001 22.116001
#> 136 0.006436894 3.144784 96 96 11.027854 11.027854
#> 137 0.006436894 3.144784 96 96 11.027854 11.027854
#> 138 0.007693063 3.064660 102 102 11.009735 44.038941
#> 139 0.006985661 3.112176 98 98 10.996466 21.992932
#> 140 0.007303857 3.095567 99 99 10.994503 10.994503
#> 141 0.007303857 3.095567 99 99 10.994503 21.989005
#> 142 0.007444717 3.070310 102 102 10.936360 21.872719
#> 143 0.007991791 3.046753 103 103 10.845795 21.691591
#> 144 0.007554303 3.071838 101 101 10.842897 32.528692
#> 145 0.007554303 3.071838 101 101 10.842897 21.685794
#> 146 0.007554303 3.071838 101 101 10.842897 21.685794
#> 147 0.007017543 3.107987 98 98 10.836518 10.836518
#> 148 0.007920229 3.035684 105 105 10.825058 21.650117
#> 149 0.008367352 3.055881 100 100 10.823063 10.823063
#> 150 0.008367352 3.055881 100 100 10.823063 21.646125
#> 151 0.008046923 3.063870 100 100 10.798666 10.798666
#> 152 0.008046923 3.063870 100 100 10.798666 21.597332
#> 153 0.008046923 3.063870 100 100 10.798666 19.005652
#> 154 0.007345618 3.082202 100 100 10.725864 21.451729
#> 155 0.007345618 3.082202 100 100 10.725864 21.451729
#> 156 0.007345618 3.082202 100 100 10.725864 21.451729
#> 157 0.007345618 3.082202 100 100 10.725864 21.451729
#> 158 0.007345618 3.082202 100 100 10.725864 21.451729
#> 159 0.007746254 3.044723 104 104 10.725049 21.450099
#> 160 0.006830676 3.097913 100 100 10.722335 21.444670
#> 161 0.006830676 3.097913 100 100 10.722335 21.444670
#> 162 0.006436894 3.144784 95 95 10.670621 10.670621
#> 163 0.006436894 3.144784 95 95 10.670621 21.341242
#> 164 0.007303857 3.095567 98 98 10.654348 10.654348
#> 165 0.007303857 3.095567 98 98 10.654348 21.308695
#> 166 0.007444717 3.070310 101 101 10.610493 21.220985
#> 167 0.008339286 3.052078 100 100 10.599504 21.199008
#> 168 0.008339286 3.052078 100 100 10.599504 21.199008
#> 169 0.007991791 3.046753 102 102 10.528152 20.377069
#> 170 0.007554303 3.071838 100 100 10.516489 10.516489
#> 171 0.007554303 3.071838 100 100 10.516489 21.032978
#> 172 0.007920229 3.035684 104 104 10.515116 21.030232
#> 173 0.007920229 3.035684 104 104 10.515116 21.030232
#> 174 0.007017543 3.107987 97 97 10.496529 10.496529
#> 175 0.008367352 3.055881 99 99 10.495711 20.991421
#> 176 0.008046923 3.063870 99 99 10.471211 20.942422
#> 177 0.006830676 3.097913 99 99 10.393638 20.787276
#> 178 0.007303857 3.095567 97 97 10.321389 10.321389
#> 179 0.007303857 3.095567 97 97 10.321389 20.642778
#> 180 0.007303857 3.095567 97 97 10.321389 20.642778
#> 181 0.007303857 3.095567 97 97 10.321389 20.642778
#> 182 0.006436894 3.144784 94 94 10.321363 10.321363
#> 183 0.006436894 3.144784 94 94 10.321363 10.321363
#> 184 0.006985661 3.112176 96 96 10.312978 20.625956
#> 185 0.006985661 3.112176 96 96 10.312978 10.312978
#> 186 0.007243730 3.076256 100 100 10.291375 20.582749
#> 187 0.007243730 3.076256 100 100 10.291375 20.582749
#> 188 0.008339286 3.052078 99 99 10.279307 20.558613
#> 189 0.007920229 3.035684 103 103 10.211181 20.422362
#> 190 0.007554303 3.071838 99 99 10.196774 10.196774
#> 191 0.007554303 3.071838 99 99 10.196774 20.393548
#> 192 0.008367352 3.055881 98 98 10.175086 10.175086
#> 193 0.008367352 3.055881 98 98 10.175086 10.175086
#> 194 0.007017543 3.107987 96 96 10.163849 10.163849
#> 195 0.007017543 3.107987 96 96 10.163849 10.163849
#> 196 0.007017543 3.107987 96 96 10.163849 20.327699
#> 197 0.008046923 3.063870 98 98 10.150512 10.150512
#> 198 0.008046923 3.063870 98 98 10.150512 20.301023
#> 199 0.008046923 3.063870 98 98 10.150512 20.301023
#> 200 0.008377248 3.027632 102 102 10.101893 20.203787
#> 201 0.008377248 3.027632 102 102 10.101893 20.203787
#> 202 0.008377248 3.027632 102 102 10.101893 20.203787
#> 203 0.007345618 3.082202 98 98 10.078347 10.078347
#> 204 0.007345618 3.082202 98 98 10.078347 20.156694
#> 205 0.007345618 3.082202 98 98 10.078347 20.156694
#> 206 0.007345618 3.082202 98 98 10.078347 20.156694
#> 207 0.007345618 3.082202 98 98 10.078347 20.156694
#> 208 0.006830676 3.097913 98 98 10.071833 10.071833
#> 209 0.006830676 3.097913 98 98 10.071833 20.143666
#> 210 0.007303857 3.095567 96 96 9.995546 9.995546
#> 211 0.007303857 3.095567 96 96 9.995546 9.995546
#> 212 0.006436894 3.144784 93 93 9.979984 9.979984
#> 213 0.006436894 3.144784 93 93 9.979984 9.979984
#> 214 0.006436894 3.144784 93 93 9.979984 9.979984
#> 215 0.007444717 3.070310 99 99 9.978524 19.313272
#> 216 0.007917341 3.037179 102 102 9.978303 20.644765
#> 217 0.007243730 3.076256 99 99 9.978060 19.956121
#> 218 0.008339286 3.052078 98 98 9.965678 9.965678
#> 219 0.007920229 3.035684 102 102 9.913195 19.826389
#> 220 0.007920229 3.035684 102 102 9.913195 19.826389
#> 221 0.007920229 3.035684 102 102 9.913195 19.826389
#> 222 0.007920229 3.035684 102 102 9.913195 19.826389
#> 223 0.007920229 3.035684 102 102 9.913195 19.826389
#> 224 0.007991791 3.046753 100 100 9.911732 19.823464
#> 225 0.007991791 3.046753 100 100 9.911732 19.823464
#> 226 0.007554303 3.071838 98 98 9.883681 19.767361
#> 227 0.007554303 3.071838 98 98 9.883681 19.767361
#> 228 0.008367352 3.055881 97 97 9.861118 19.722236
#> 229 0.008945098 3.008082 102 102 9.854156 19.708313
#> 230 0.007746254 3.044723 101 101 9.810585 19.621169
#> 231 0.008377248 3.027632 101 101 9.805012 19.610025
#> 232 0.009197813 2.994628 103 103 9.803541 19.607081
#> 233 0.009197813 2.994628 103 103 9.803541 49.017704
#> 234 0.007345618 3.082202 97 97 9.764727 19.529454
#> 235 0.006830676 3.097913 97 97 9.756844 9.922214
#> 236 0.006830676 3.097913 97 97 9.756844 9.922214
#> 237 0.006830676 3.097913 97 97 9.756844 19.513688
#> 238 0.007917341 3.037179 101 101 9.684143 19.368287
#> 239 0.007917341 3.037179 101 101 9.684143 19.368287
#> 240 0.007917341 3.037179 101 101 9.684143 19.368287
#> 241 0.007303857 3.095567 95 95 9.676740 19.353479
#> 242 0.007303857 3.095567 95 95 9.676740 19.353479
#> 243 0.007444717 3.070310 98 98 9.672282 19.344563
#> 244 0.007444717 3.070310 98 98 9.672282 19.344563
#> 245 0.007243730 3.076256 98 98 9.671249 19.342497
#> 246 0.006985661 3.112176 94 94 9.658914 19.317827
#> 247 0.006985661 3.112176 94 94 9.658914 9.658914
#> 248 0.008339286 3.052078 97 97 9.658548 25.112225
#> 249 0.008339286 3.052078 97 97 9.658548 38.634192
#> 250 0.006436894 3.144784 92 92 9.646387 9.646387
#> 251 0.007554303 3.071838 97 97 9.577137 9.577137
#> 252 0.007554303 3.071838 97 97 9.577137 19.154273
#> 253 0.007554303 3.071838 97 97 9.577137 19.154273
#> 254 0.008945098 3.008082 101 101 9.566399 19.132797
#> 255 0.008367352 3.055881 96 96 9.553735 9.553735
#> 256 0.008367352 3.055881 96 96 9.553735 28.661204
#> 257 0.008367352 3.055881 96 96 9.553735 19.107469
#> 258 0.008046923 3.063870 96 96 9.529091 19.058181
#> 259 0.008046923 3.063870 96 96 9.529091 9.529091
#> 260 0.009197813 2.994628 102 102 9.521263 19.042526
#> 261 0.009197813 2.994628 102 102 9.521263 19.042526
#> 262 0.009197813 2.994628 102 102 9.521263 19.042526
#> 263 0.007017543 3.107987 94 94 9.520083 9.520083
#> 264 0.008377248 3.027632 100 100 9.514032 22.833678
#> 265 0.008377248 3.027632 100 100 9.514032 19.028065
#> 266 0.008377248 3.027632 100 100 9.514032 19.028065
#> 267 0.007345618 3.082202 96 96 9.457768 9.457768
#> 268 0.007345618 3.082202 96 96 9.457768 18.915536
#> 269 0.007345618 3.082202 96 96 9.457768 18.915536
#> 270 0.006830676 3.097913 96 96 9.448594 9.448594
#> 271 0.006830676 3.097913 96 96 9.448594 9.448594
#> 272 0.006830676 3.097913 96 96 9.448594 18.897188
#> 273 0.006830676 3.097913 96 96 9.448594 18.897188
#> 274 0.006830676 3.097913 96 96 9.448594 18.897188
#> 275 0.007917341 3.037179 100 100 9.395858 56.375146
#> 276 0.007444717 3.070310 97 97 9.372441 18.744882
#> 277 0.007444717 3.070310 97 97 9.372441 18.744882
#> 278 0.007243730 3.076256 97 97 9.370869 18.741738
#> 279 0.007243730 3.076256 97 97 9.370869 18.741738
#> 280 0.007243730 3.076256 97 97 9.370869 18.741738
#> 281 0.007303857 3.095567 94 94 9.364888 9.364888
#> 282 0.007303857 3.095567 94 94 9.364888 9.364888
#> 283 0.007303857 3.095567 94 94 9.364888 18.729776
#> 284 0.008339286 3.052078 96 96 9.357847 9.357847
#> 285 0.006985661 3.112176 93 93 9.342702 9.342702
#> 286 0.006985661 3.112176 93 93 9.342702 18.685405
#> 287 0.006436894 3.144784 91 91 9.320478 9.320478
#> 288 0.006436894 3.144784 91 91 9.320478 18.640955
#> 289 0.007991791 3.046753 98 98 9.320036 18.640072
#> 290 0.008945098 3.008082 100 100 9.284306 18.568611
#> 291 0.008367352 3.055881 95 95 9.252864 18.505727
#> 292 0.007746254 3.044723 99 99 9.230982 18.461963
#> 293 0.008377248 3.027632 99 99 9.228893 36.915571
#> 294 0.008377248 3.027632 99 99 9.228893 18.457786
#> 295 0.008046923 3.063870 95 95 9.228224 18.456448
#> 296 0.008046923 3.063870 95 95 9.228224 9.228224
#> 297 0.008046923 3.063870 95 95 9.228224 18.456448
#> 298 0.008046923 3.063870 95 95 9.228224 9.228224
#> 299 0.007017543 3.107987 93 93 9.208829 9.208829
#> 300 0.007345618 3.082202 95 95 9.157395 18.314790
#> 301 0.007345618 3.082202 95 95 9.157395 18.314790
#> 302 0.006830676 3.097913 95 95 9.147008 9.302042
#> 303 0.007444717 3.070310 96 96 9.078933 18.157865
#> 304 0.007444717 3.070310 96 96 9.078933 18.157865
#> 305 0.007243730 3.076256 96 96 9.076850 18.153700
#> 306 0.008339286 3.052078 95 95 9.063506 18.127013
#> 307 0.008339286 3.052078 95 95 9.063506 18.127013
#> 308 0.007303857 3.095567 93 93 9.059912 18.119824
#> 309 0.007920229 3.035684 99 99 9.054324 18.108649
#> 310 0.006985661 3.112176 92 92 9.033592 18.067184
#> 311 0.006985661 3.112176 92 92 9.033592 9.033592
#> 312 0.006985661 3.112176 92 92 9.033592 9.033592
#> 313 0.006985661 3.112176 92 92 9.033592 9.033592
#> 314 0.007991791 3.046753 97 97 9.033297 18.066595
#> 315 0.007991791 3.046753 97 97 9.033297 18.066595
#> 316 0.006436894 3.144784 90 90 9.002160 9.002160
#> 317 0.006436894 3.144784 90 90 9.002160 9.002160
#> 318 0.006436894 3.144784 90 90 9.002160 9.002160
#> 319 0.007554303 3.071838 95 95 8.983412 17.966823
#> 320 0.007554303 3.071838 95 95 8.983412 8.983412
#> 321 0.007554303 3.071838 95 95 8.983412 17.966823
#> 322 0.009197813 2.994628 100 100 8.973053 17.367200
#> 323 0.009197813 2.994628 100 100 8.973053 44.865266
#> 324 0.008367352 3.055881 94 94 8.958434 17.916868
#> 325 0.008367352 3.055881 94 94 8.958434 17.916868
#> 326 0.008046923 3.063870 94 94 8.933823 8.933823
#> 327 0.008046923 3.063870 94 94 8.933823 17.867646
#> 328 0.008046923 3.063870 94 94 8.933823 17.867646
#> 329 0.007017543 3.107987 92 92 8.904551 8.904551
#> 330 0.007345618 3.082202 94 94 8.863534 8.863534
#> 331 0.007693063 3.064660 95 95 8.854228 17.708455
#> 332 0.006830676 3.097913 94 94 8.852008 17.704016
#> 333 0.007917341 3.037179 98 98 8.836666 18.282758
#> 334 0.007243730 3.076256 95 95 8.789122 17.578244
#> 335 0.007243730 3.076256 95 95 8.789122 17.578244
#> 336 0.007920229 3.035684 98 98 8.779532 17.559064
#> 337 0.008339286 3.052078 94 94 8.775455 17.550910
#> 338 0.008339286 3.052078 94 94 8.775455 17.550910
#> 339 0.007303857 3.095567 92 92 8.761731 8.761731
#> 340 0.007303857 3.095567 92 92 8.761731 17.523462
#> 341 0.006985661 3.112176 91 91 8.731498 8.731498
#> 342 0.006985661 3.112176 91 91 8.731498 8.731498
#> 343 0.006985661 3.112176 91 91 8.731498 34.925990
#> 344 0.009197813 2.994628 99 99 8.707015 17.414029
#> 345 0.009197813 2.994628 99 99 8.707015 17.414029
#> 346 0.007554303 3.071838 94 94 8.696087 8.843479
#> 347 0.007554303 3.071838 94 94 8.696087 17.392175
#> 348 0.007554303 3.071838 94 94 8.696087 17.392175
#> 349 0.006436894 3.144784 89 89 8.691338 8.691338
#> 350 0.006436894 3.144784 89 89 8.691338 8.691338
#> 351 0.008377248 3.027632 97 97 8.675895 17.351791
#> 352 0.008377248 3.027632 97 97 8.675895 17.351791
#> 353 0.008377248 3.027632 97 97 8.675895 17.351791
#> 354 0.007746254 3.044723 97 97 8.674833 16.789999
#> 355 0.007746254 3.044723 97 97 8.674833 17.349665
#> 356 0.008367352 3.055881 93 93 8.670374 8.670374
#> 357 0.008367352 3.055881 93 93 8.670374 8.670374
#> 358 0.008367352 3.055881 93 93 8.670374 8.670374
#> 359 0.008367352 3.055881 93 93 8.670374 17.340747
#> 360 0.008046923 3.063870 93 93 8.645815 17.291630
#> 361 0.008046923 3.063870 93 93 8.645815 8.645815
#> 362 0.007345618 3.082202 93 93 8.576111 8.576111
#> 363 0.007345618 3.082202 93 93 8.576111 8.576111
#> 364 0.007345618 3.082202 93 93 8.576111 17.152222
#> 365 0.007345618 3.082202 93 93 8.576111 17.152222
#> 366 0.007345618 3.082202 93 93 8.576111 17.152222
#> 367 0.007345618 3.082202 93 93 8.576111 17.152222
#> 368 0.007345618 3.082202 93 93 8.576111 17.152222
#> 369 0.007345618 3.082202 93 93 8.576111 17.152222
#> 370 0.007693063 3.064660 94 94 8.571686 17.143372
#> 371 0.007693063 3.064660 94 94 8.571686 17.143372
#> 372 0.007693063 3.064660 94 94 8.571686 17.143372
#> 373 0.006830676 3.097913 93 93 8.563520 17.127039
#> 374 0.006830676 3.097913 93 93 8.563520 17.127039
#> 375 0.007444717 3.070310 94 94 8.510631 17.021263
#> 376 0.007920229 3.035684 97 97 8.510388 17.020777
#> 377 0.007243730 3.076256 94 94 8.507614 17.015229
#> 378 0.008339286 3.052078 93 93 8.493624 8.493624
#> 379 0.008339286 3.052078 93 93 8.493624 16.987248
#> 380 0.007991791 3.046753 95 95 8.477717 16.955433
#> 381 0.008945098 3.008082 97 97 8.471449 16.942899
#> 382 0.008945098 3.008082 97 97 8.471449 16.942899
#> 383 0.007303857 3.095567 91 91 8.470265 16.940530
#> 384 0.007303857 3.095567 91 91 8.470265 16.940530
#> 385 0.006985661 3.112176 90 90 8.436334 8.436334
#> 386 0.006985661 3.112176 90 90 8.436334 8.436334
#> 387 0.006985661 3.112176 90 90 8.436334 16.872668
#> 388 0.006985661 3.112176 90 90 8.436334 16.872668
#> 389 0.006985661 3.112176 90 90 8.436334 8.436334
#> 390 0.008753122 3.011747 97 97 8.429806 16.859612
#> 391 0.007554303 3.071838 93 93 8.415027 16.830053
#> 392 0.007554303 3.071838 93 93 8.415027 8.415027
#> 393 0.007554303 3.071838 93 93 8.415027 16.830053
#> 394 0.008377248 3.027632 96 96 8.407918 16.815835
#> 395 0.007746254 3.044723 96 96 8.405399 16.810798
#> 396 0.007746254 3.044723 96 96 8.405399 16.810798
#> 397 0.007746254 3.044723 96 96 8.405399 16.810798
#> 398 0.007746254 3.044723 96 96 8.405399 16.810798
#> 399 0.007746254 3.044723 96 96 8.405399 16.810798
#> 400 0.008367352 3.055881 92 92 8.388611 16.777223
#> 401 0.006436894 3.144784 88 88 8.387917 8.387917
#> 402 0.006436894 3.144784 88 88 8.387917 16.775835
#> 403 0.006436894 3.144784 88 88 8.387917 16.775835
#> 404 0.006436894 3.144784 88 88 8.387917 16.775835
#> 405 0.008046923 3.063870 92 92 8.364129 8.364129
#> 406 0.008046923 3.063870 92 92 8.364129 16.728257
#> 407 0.008046923 3.063870 92 92 8.364129 16.728257
#> 408 0.008046923 3.063870 92 92 8.364129 8.364129
#> 409 0.007017543 3.107987 90 90 8.316590 41.582952
#> 410 0.007917341 3.037179 96 96 8.300247 16.600493
#> 411 0.007345618 3.082202 92 92 8.295051 8.295051
#> 412 0.007345618 3.082202 92 92 8.295051 16.590102
#> 413 0.007345618 3.082202 92 92 8.295051 8.295051
#> 414 0.007345618 3.082202 92 92 8.295051 16.590102
#> 415 0.006830676 3.097913 92 92 8.281466 16.562932
#> 416 0.006830676 3.097913 92 92 8.281466 16.562932
#> 417 0.006830676 3.097913 92 92 8.281466 16.562932
#> 418 0.007920229 3.035684 96 96 8.246835 24.740504
#> 419 0.007920229 3.035684 96 96 8.246835 15.961615
#> 420 0.007444717 3.070310 93 93 8.235699 16.471399
#> 421 0.007444717 3.070310 93 93 8.235699 32.942797
#> 422 0.007444717 3.070310 93 93 8.235699 16.471399
#> 423 0.007243730 3.076256 93 93 8.232256 16.464513
#> 424 0.007243730 3.076256 93 93 8.232256 16.464513
#> 425 0.007243730 3.076256 93 93 8.232256 16.464513
#> 426 0.008945098 3.008082 96 96 8.211450 16.422900
#> 427 0.008945098 3.008082 96 96 8.211450 16.422900
#> 428 0.009208543 3.001584 96 96 8.206234 16.412468
#> 429 0.009197813 2.994628 97 97 8.190804 16.381607
#> 430 0.009197813 2.994628 97 97 8.190804 32.763215
#> 431 0.009197813 2.994628 97 97 8.190804 16.381607
#> 432 0.009197813 2.994628 97 97 8.190804 40.954018
#> 433 0.007303857 3.095567 90 90 8.185434 8.185434
#> 434 0.007303857 3.095567 90 90 8.185434 24.556303
#> 435 0.007303857 3.095567 90 90 8.185434 16.370869
#> 436 0.009413393 2.981889 98 98 8.153807 16.307615
#> 437 0.006985661 3.112176 89 89 8.148017 8.148017
#> 438 0.008377248 3.027632 95 95 8.145540 16.291081
#> 439 0.008377248 3.027632 95 95 8.145540 16.291081
#> 440 0.008377248 3.027632 95 95 8.145540 16.291081
#> 441 0.008377248 3.027632 95 95 8.145540 16.291081
#> 442 0.007746254 3.044723 95 95 8.141643 16.283286
#> 443 0.007746254 3.044723 95 95 8.141643 24.424929
#> 444 0.007746254 3.044723 95 95 8.141643 16.283286
#> 445 0.007554303 3.071838 92 92 8.140158 16.280316
#> 446 0.007554303 3.071838 92 92 8.140158 16.280316
#> 447 0.008367352 3.055881 91 91 8.113076 7.980075
#> 448 0.008367352 3.055881 91 91 8.113076 8.113076
#> 449 0.008367352 3.055881 91 91 8.113076 8.113076
#> 450 0.008367352 3.055881 91 91 8.113076 16.226152
#> 451 0.008367352 3.055881 91 91 8.113076 16.226152
#> 452 0.008367352 3.055881 91 91 8.113076 16.226152
#> 453 0.006436894 3.144784 87 87 8.091802 16.183604
#> 454 0.006436894 3.144784 87 87 8.091802 8.091802
#> 455 0.006436894 3.144784 87 87 8.091802 8.091802
#> 456 0.006436894 3.144784 87 87 8.091802 8.091802
#> 457 0.006436894 3.144784 87 87 8.091802 8.091802
#> 458 0.006436894 3.144784 87 87 8.091802 8.091802
#> 459 0.006436894 3.144784 87 87 8.091802 8.091802
#> 460 0.006436894 3.144784 87 87 8.091802 8.091802
#> 461 0.008046923 3.063870 91 91 8.088691 8.088691
#> 462 0.008046923 3.063870 91 91 8.088691 8.088691
#> 463 0.008046923 3.063870 91 91 8.088691 16.177382
#> 464 0.008046923 3.063870 91 91 8.088691 8.088691
#> 465 0.008046923 3.063870 91 91 8.088691 16.177382
#> 466 0.008046923 3.063870 91 91 8.088691 32.354764
#> 467 0.007917341 3.037179 95 95 8.040426 15.562114
#> 468 0.007017543 3.107987 89 89 8.032742 8.032742
#> 469 0.007017543 3.107987 89 89 8.032742 8.032742
#> 470 0.007345618 3.082202 91 91 8.020281 8.156218
#> 471 0.007345618 3.082202 91 91 8.020281 8.020281
#> 472 0.007345618 3.082202 91 91 8.020281 8.020281
#> 473 0.007345618 3.082202 91 91 8.020281 16.040563
#> 474 0.007345618 3.082202 91 91 8.020281 16.040563
#> 475 0.007345618 3.082202 91 91 8.020281 48.121688
#> 476 0.007345618 3.082202 91 91 8.020281 16.040563
#> 477 0.006830676 3.097913 91 91 8.005771 16.011542
#> 478 0.007920229 3.035684 95 95 7.988811 15.977621
#> 479 0.007920229 3.035684 95 95 7.988811 15.977621
#> 480 0.007444717 3.070310 92 92 7.966820 15.933640
#> 481 0.007444717 3.070310 92 92 7.966820 15.933640
#> 482 0.007444717 3.070310 92 92 7.966820 15.933640
#> 483 0.007444717 3.070310 92 92 7.966820 15.933640
#> 484 0.007444717 3.070310 92 92 7.966820 15.933640
#> 485 0.007444717 3.070310 92 92 7.966820 15.933640
#> 486 0.007243730 3.076256 92 92 7.962977 15.925955
#> 487 0.007243730 3.076256 92 92 7.962977 15.925955
#> 488 0.007243730 3.076256 92 92 7.962977 26.437085
#> 489 0.008945098 3.008082 95 95 7.956832 15.913665
#> 490 0.009208543 3.001584 95 95 7.952319 15.904639
#> 491 0.009208543 3.001584 95 95 7.952319 15.904639
#> 492 0.009208543 3.001584 95 95 7.952319 15.904639
#> 493 0.008339286 3.052078 91 91 7.948344 7.948344
#> 494 0.008339286 3.052078 91 91 7.948344 15.896688
#> 495 0.008339286 3.052078 91 91 7.948344 15.896688
#> 496 0.008339286 3.052078 91 91 7.948344 15.896688
#> 497 0.007991791 3.046753 93 93 7.945567 15.891134
#> 498 0.009197813 2.994628 96 96 7.940524 15.881049
#> 499 0.009197813 2.994628 96 96 7.940524 15.881049
#> 500 0.008753122 3.011747 95 95 7.917114 15.834228
#> 501 0.008753122 3.011747 95 95 7.917114 15.834228
#> 502 0.007303857 3.095567 89 89 7.907159 7.907159
#> 503 0.007303857 3.095567 89 89 7.907159 15.814319
#> 504 0.008377248 3.027632 94 94 7.888704 15.777408
#> 505 0.007746254 3.044723 94 94 7.883504 16.310697
#> 506 0.007746254 3.044723 94 94 7.883504 15.767007
#> 507 0.007746254 3.044723 94 94 7.883504 15.767007
#> 508 0.007554303 3.071838 91 91 7.871411 15.742821
#> 509 0.007554303 3.071838 91 91 7.871411 23.614232
#> 510 0.007554303 3.071838 91 91 7.871411 15.742821
#> 511 0.007554303 3.071838 91 91 7.871411 15.742821
#> 512 0.007554303 3.071838 91 91 7.871411 15.742821
#> 513 0.006985661 3.112176 88 88 7.866462 7.866462
#> 514 0.006985661 3.112176 88 88 7.866462 7.866462
#> 515 0.006985661 3.112176 88 88 7.866462 15.732924
#> 516 0.008367352 3.055881 90 90 7.843695 7.843695
#> 517 0.008367352 3.055881 90 90 7.843695 15.687391
#> 518 0.008367352 3.055881 90 90 7.843695 15.687391
#> 519 0.008046923 3.063870 90 90 7.819430 15.638860
#> 520 0.008046923 3.063870 90 90 7.819430 15.638860
#> 521 0.008046923 3.063870 90 90 7.819430 15.638860
#> 522 0.006436894 3.144784 86 86 7.802898 7.802898
#> 523 0.006436894 3.144784 86 86 7.802898 7.802898
#> 524 0.006436894 3.144784 86 86 7.802898 7.802898
#> 525 0.006436894 3.144784 86 86 7.802898 15.605796
#> 526 0.007917341 3.037179 94 94 7.786117 15.572234
#> 527 0.007693063 3.064660 91 91 7.760613 15.521226
#> 528 0.007693063 3.064660 91 91 7.760613 16.056441
#> 529 0.007017543 3.107987 88 88 7.755537 7.755537
#> 530 0.007017543 3.107987 88 88 7.755537 7.755537
#> 531 0.007017543 3.107987 88 88 7.755537 7.755537
#> 532 0.007345618 3.082202 90 90 7.751727 7.751727
#> 533 0.007345618 3.082202 90 90 7.751727 7.751727
#> 534 0.007345618 3.082202 90 90 7.751727 15.503454
#> 535 0.007345618 3.082202 90 90 7.751727 15.503454
#> 536 0.007345618 3.082202 90 90 7.751727 15.503454
#> 537 0.007345618 3.082202 90 90 7.751727 46.510363
#> 538 0.007345618 3.082202 90 90 7.751727 15.503454
#> 539 0.006830676 3.097913 90 90 7.736360 15.472719
#> 540 0.006830676 3.097913 90 90 7.736360 15.472719
#> 541 0.006830676 3.097913 90 90 7.736360 15.472719
#> 542 0.007920229 3.035684 94 94 7.736257 15.472513
#> 543 0.007920229 3.035684 94 94 7.736257 15.472513
#> 544 0.007920229 3.035684 94 94 7.736257 15.472513
#> 545 0.007920229 3.035684 94 94 7.736257 15.472513
#> 546 0.007920229 3.035684 94 94 7.736257 15.472513
#> 547 0.007920229 3.035684 94 94 7.736257 15.472513
#> 548 0.007920229 3.035684 94 94 7.736257 14.973400
#> 549 0.007920229 3.035684 94 94 7.736257 15.472513
#> 550 0.007920229 3.035684 94 94 7.736257 15.472513
#> 551 0.008945098 3.008082 94 94 7.707540 15.415081
#> 552 0.007444717 3.070310 91 91 7.703924 15.407848
#> 553 0.007444717 3.070310 91 91 7.703924 15.407848
#> 554 0.009208543 3.001584 94 94 7.703699 15.407397
#> 555 0.009208543 3.001584 94 94 7.703699 15.407397
#> 556 0.009208543 3.001584 94 94 7.703699 15.407397
#> 557 0.009208543 3.001584 94 94 7.703699 15.407397
#> 558 0.009197813 2.994628 95 95 7.695392 15.390784
#> 559 0.009197813 2.994628 95 95 7.695392 15.390784
#> 560 0.009197813 2.994628 95 95 7.695392 30.781567
#> 561 0.009197813 2.994628 95 95 7.695392 15.390784
#> 562 0.009197813 2.994628 95 95 7.695392 15.390784
#> 563 0.009197813 2.994628 95 95 7.695392 15.390784
#> 564 0.009197813 2.994628 95 95 7.695392 15.390784
#> 565 0.009197813 2.994628 95 95 7.695392 15.390784
#> 566 0.009197813 2.994628 95 95 7.695392 30.781567
#> 567 0.007991791 3.046753 92 92 7.688118 15.376235
#> 568 0.007991791 3.046753 92 92 7.688118 15.376235
#> 569 0.008339286 3.052078 90 90 7.684756 15.369513
#> 570 0.008339286 3.052078 90 90 7.684756 15.369513
#> 571 0.008339286 3.052078 90 90 7.684756 15.369513
#> 572 0.008753122 3.011747 94 94 7.668769 15.337538
#> 573 0.008377248 3.027632 93 93 7.637348 61.098787
#> 574 0.008377248 3.027632 93 93 7.637348 15.274697
#> 575 0.008377248 3.027632 93 93 7.637348 15.274697
#> 576 0.008377248 3.027632 93 93 7.637348 76.373484
#> 577 0.008377248 3.027632 93 93 7.637348 15.274697
#> 578 0.008377248 3.027632 93 93 7.637348 15.274697
#> 579 0.007303857 3.095567 88 88 7.635360 7.635360
#> 580 0.007303857 3.095567 88 88 7.635360 7.635360
#> 581 0.007303857 3.095567 88 88 7.635360 15.270719
#> 582 0.007303857 3.095567 88 88 7.635360 15.270719
#> 583 0.007303857 3.095567 88 88 7.635360 15.270719
#> 584 0.007303857 3.095567 88 88 7.635360 15.270719
#> 585 0.007746254 3.044723 93 93 7.630919 15.261837
#> 586 0.007746254 3.044723 93 93 7.630919 15.788107
#> 587 0.007746254 3.044723 93 93 7.630919 15.261837
#> 588 0.007746254 3.044723 93 93 7.630919 15.261837
#> 589 0.007746254 3.044723 93 93 7.630919 15.261837
#> 590 0.007746254 3.044723 93 93 7.630919 15.261837
#> 591 0.007746254 3.044723 93 93 7.630919 15.261837
#> 592 0.007554303 3.071838 90 90 7.608712 15.217425
#> 593 0.007554303 3.071838 90 90 7.608712 15.217425
#> 594 0.007554303 3.071838 90 90 7.608712 15.217425
#> 595 0.006985661 3.112176 87 87 7.591584 7.591584
#> 596 0.006985661 3.112176 87 87 7.591584 7.591584
#> 597 0.006985661 3.112176 87 87 7.591584 7.591584
#> 598 0.006985661 3.112176 87 87 7.591584 7.591584
#> 599 0.008367352 3.055881 89 89 7.580399 7.580399
#> 600 0.008367352 3.055881 89 89 7.580399 7.580399
#> 601 0.008046923 3.063870 89 89 7.556273 15.112546
#> 602 0.008046923 3.063870 89 89 7.556273 15.112546
#> 603 0.008046923 3.063870 89 89 7.556273 15.112546
#> 604 0.008046923 3.063870 89 89 7.556273 15.112546
#> 605 0.008046923 3.063870 89 89 7.556273 15.112546
#> 606 0.007917341 3.037179 93 93 7.537260 15.074521
#> 607 0.007917341 3.037179 93 93 7.537260 22.611781
#> 608 0.007917341 3.037179 93 93 7.537260 15.074521
#> 609 0.006436894 3.144784 85 85 7.521110 7.521110
#> 610 0.006436894 3.144784 85 85 7.521110 7.521110
#> 611 0.006436894 3.144784 85 85 7.521110 7.521110
#> 612 0.006436894 3.144784 85 85 7.521110 7.521110
#> 613 0.006436894 3.144784 85 85 7.521110 15.042219
#> 614 0.006436894 3.144784 85 85 7.521110 15.042219
#> 615 0.006436894 3.144784 85 85 7.521110 7.521110
#> 616 0.007693063 3.064660 90 90 7.502208 15.004416
#> 617 0.007345618 3.082202 89 89 7.489315 7.489315
#> 618 0.007345618 3.082202 89 89 7.489315 7.489315
#> 619 0.007345618 3.082202 89 89 7.489315 29.957259
#> 620 0.007920229 3.035684 93 93 7.489113 29.956454
#> 621 0.007017543 3.107987 87 87 7.484894 7.484894
#> 622 0.006830676 3.097913 89 89 7.473156 7.599819
#> 623 0.008945098 3.008082 93 93 7.463517 14.927035
#> 624 0.008945098 3.008082 93 93 7.463517 14.927035
#> 625 0.008945098 3.008082 93 93 7.463517 22.390552
#> 626 0.008945098 3.008082 93 93 7.463517 14.927035
#> 627 0.009208543 3.001584 93 93 7.460316 29.841263
#> 628 0.009208543 3.001584 93 93 7.460316 14.920632
#> 629 0.009208543 3.001584 93 93 7.460316 14.920632
#> 630 0.009197813 2.994628 94 94 7.455352 14.910705
#> 631 0.007444717 3.070310 90 90 7.446941 14.893882
#> 632 0.007444717 3.070310 90 90 7.446941 14.893882
#> 633 0.007444717 3.070310 90 90 7.446941 14.893882
#> 634 0.007444717 3.070310 90 90 7.446941 14.893882
#> 635 0.007243730 3.076256 90 90 7.442377 14.884753
#> 636 0.007243730 3.076256 90 90 7.442377 14.884753
#> 637 0.007991791 3.046753 91 91 7.436333 14.872665
#> 638 0.007991791 3.046753 91 91 7.436333 14.872665
#> 639 0.007991791 3.046753 91 91 7.436333 14.872665
#> 640 0.007991791 3.046753 91 91 7.436333 14.872665
#> 641 0.007991791 3.046753 91 91 7.436333 14.872665
#> 642 0.007991791 3.046753 91 91 7.436333 14.872665
#> 643 0.009413393 2.981889 95 95 7.431861 29.727445
#> 644 0.009413393 2.981889 95 95 7.431861 37.159306
#> 645 0.008377248 3.027632 92 92 7.391414 14.782827
#> 646 0.008377248 3.027632 92 92 7.391414 14.782827
#> 647 0.008377248 3.027632 92 92 7.391414 14.782827
#> 648 0.008377248 3.027632 92 92 7.391414 14.782827
#> 649 0.007746254 3.044723 92 92 7.383826 15.276882
#> 650 0.007746254 3.044723 92 92 7.383826 14.291277
#> 651 0.007746254 3.044723 92 92 7.383826 14.767653
#> 652 0.007303857 3.095567 87 87 7.369956 7.369956
#> 653 0.007303857 3.095567 87 87 7.369956 7.369956
#> 654 0.007303857 3.095567 87 87 7.369956 14.739912
#> 655 0.007554303 3.071838 89 89 7.351993 14.703985
#> 656 0.006985661 3.112176 86 86 7.323299 14.646599
#> 657 0.006985661 3.112176 86 86 7.323299 7.323299
#> 658 0.006985661 3.112176 86 86 7.323299 7.323299
#> 659 0.006985661 3.112176 86 86 7.323299 7.323299
#> 660 0.008367352 3.055881 88 88 7.323114 7.323114
#> 661 0.008367352 3.055881 88 88 7.323114 14.646229
#> 662 0.008367352 3.055881 88 88 7.323114 21.969343
#> 663 0.008367352 3.055881 88 88 7.323114 14.646229
#> 664 0.008367352 3.055881 88 88 7.323114 14.646229
#> 665 0.008367352 3.055881 88 88 7.323114 14.646229
#> 666 0.008046923 3.063870 88 88 7.299149 7.299149
#> 667 0.008046923 3.063870 88 88 7.299149 14.598298
#> 668 0.007917341 3.037179 92 92 7.293796 14.587592
#> 669 0.007917341 3.037179 92 92 7.293796 14.587592
#> 670 0.007693063 3.064660 89 89 7.249663 14.499326
#> 671 0.007693063 3.064660 89 89 7.249663 14.499326
#> 672 0.007920229 3.035684 92 92 7.247321 14.494642
#> 673 0.007920229 3.035684 92 92 7.247321 21.741963
#> 674 0.007920229 3.035684 92 92 7.247321 14.494642
#> 675 0.007920229 3.035684 92 92 7.247321 28.989284
#> 676 0.007920229 3.035684 92 92 7.247321 14.494642
#> 677 0.007920229 3.035684 92 92 7.247321 14.494642
#> 678 0.007920229 3.035684 92 92 7.247321 14.494642
#> 679 0.007920229 3.035684 92 92 7.247321 14.494642
#> 680 0.006436894 3.144784 84 84 7.246343 7.246343
#> 681 0.006436894 3.144784 84 84 7.246343 7.246343
#> 682 0.006436894 3.144784 84 84 7.246343 14.492685
#> 683 0.006436894 3.144784 84 84 7.246343 14.492685
#> 684 0.006436894 3.144784 84 84 7.246343 14.492685
#> 685 0.006436894 3.144784 84 84 7.246343 7.246343
#> 686 0.006436894 3.144784 84 84 7.246343 14.492685
#> 687 0.006436894 3.144784 84 84 7.246343 14.492685
#> 688 0.006436894 3.144784 84 84 7.246343 14.492685
#> 689 0.007345618 3.082202 88 88 7.232970 7.232970
#> 690 0.007345618 3.082202 88 88 7.232970 7.232970
#> 691 0.007345618 3.082202 88 88 7.232970 14.465941
#> 692 0.007345618 3.082202 88 88 7.232970 7.232970
#> 693 0.007345618 3.082202 88 88 7.232970 14.465941
#> 694 0.007345618 3.082202 88 88 7.232970 14.465941
#> 695 0.007345618 3.082202 88 88 7.232970 28.931881
#> 696 0.007345618 3.082202 88 88 7.232970 43.397822
#> 697 0.007345618 3.082202 88 88 7.232970 28.931881
#> 698 0.008945098 3.008082 92 92 7.224707 14.449414
#> 699 0.008945098 3.008082 92 92 7.224707 43.348242
#> 700 0.009208543 3.001584 92 92 7.222115 14.444231
#> 701 0.009208543 3.001584 92 92 7.222115 14.942307
#> 702 0.009208543 3.001584 92 92 7.222115 14.444231
#> 703 0.009208543 3.001584 92 92 7.222115 14.444231
#> 704 0.007017543 3.107987 86 86 7.220729 7.220729
#> 705 0.007017543 3.107987 86 86 7.220729 7.220729
#> 706 0.007017543 3.107987 86 86 7.220729 7.220729
#> 707 0.007017543 3.107987 86 86 7.220729 7.220729
#> 708 0.007017543 3.107987 86 86 7.220729 7.220729
#> 709 0.007017543 3.107987 86 86 7.220729 7.220729
#> 710 0.007017543 3.107987 86 86 7.220729 7.220729
#> 711 0.007017543 3.107987 86 86 7.220729 7.220729
#> 712 0.007017543 3.107987 86 86 7.220729 7.220729
#> 713 0.009197813 2.994628 93 93 7.220353 14.440705
#> 714 0.006830676 3.097913 88 88 7.216083 7.216083
#> 715 0.006830676 3.097913 88 88 7.216083 7.216083
#> 716 0.006830676 3.097913 88 88 7.216083 14.432166
#> 717 0.006830676 3.097913 88 88 7.216083 14.432166
#> 718 0.006830676 3.097913 88 88 7.216083 14.432166
#> 719 0.006830676 3.097913 88 88 7.216083 14.432166
#> 720 0.006830676 3.097913 88 88 7.216083 14.432166
#> 721 0.007444717 3.070310 89 89 7.195803 14.391605
#> 722 0.007444717 3.070310 89 89 7.195803 14.391605
#> 723 0.007243730 3.076256 89 89 7.190914 14.381829
#> 724 0.007991791 3.046753 90 90 7.190148 14.380295
#> 725 0.008339286 3.052078 88 88 7.175337 7.175337
#> 726 0.008339286 3.052078 88 88 7.175337 7.175337
#> 727 0.008339286 3.052078 88 88 7.175337 14.350674
#> 728 0.008377248 3.027632 91 91 7.150840 14.301680
#> 729 0.008377248 3.027632 91 91 7.150840 14.301680
#> 730 0.008377248 3.027632 91 91 7.150840 21.452519
#> 731 0.008377248 3.027632 91 91 7.150840 14.301680
#> 732 0.008377248 3.027632 91 91 7.150840 14.301680
#> 733 0.007746254 3.044723 91 91 7.142165 14.284331
#> 734 0.007746254 3.044723 91 91 7.142165 14.284331
#> 735 0.007746254 3.044723 91 91 7.142165 14.284331
#> 736 0.007746254 3.044723 91 91 7.142165 14.284331
#> 737 0.007746254 3.044723 91 91 7.142165 14.284331
#> 738 0.007746254 3.044723 91 91 7.142165 14.284331
#> 739 0.007746254 3.044723 91 91 7.142165 14.284331
#> 740 0.007303857 3.095567 86 86 7.110869 28.443476
#> 741 0.007303857 3.095567 86 86 7.110869 14.221738
#> 742 0.007303857 3.095567 86 86 7.110869 14.221738
#> 743 0.007554303 3.071838 88 88 7.101180 7.101180
#> 744 0.007554303 3.071838 88 88 7.101180 14.692097
#> 745 0.007554303 3.071838 88 88 7.101180 14.202360
#> 746 0.007554303 3.071838 88 88 7.101180 14.202360
#> 747 0.008367352 3.055881 87 87 7.071771 7.071771
#> 748 0.008367352 3.055881 87 87 7.071771 14.143542
#> 749 0.008367352 3.055881 87 87 7.071771 63.645941
#> 750 0.008367352 3.055881 87 87 7.071771 14.143542
#> 751 0.008367352 3.055881 87 87 7.071771 14.143542
#> 752 0.008367352 3.055881 87 87 7.071771 14.143542
#> 753 0.008367352 3.055881 87 87 7.071771 14.143542
#> 754 0.006985661 3.112176 85 85 7.061524 7.061524
#> 755 0.006985661 3.112176 85 85 7.061524 7.061524
#> 756 0.006985661 3.112176 85 85 7.061524 7.061524
#> 757 0.006985661 3.112176 85 85 7.061524 14.123047
#> 758 0.006985661 3.112176 85 85 7.061524 7.061524
#> 759 0.007917341 3.037179 91 91 7.055663 14.111326
#> 760 0.007917341 3.037179 91 91 7.055663 13.656122
#> 761 0.007917341 3.037179 91 91 7.055663 14.111326
#> 762 0.007917341 3.037179 91 91 7.055663 14.111326
#> 763 0.008046923 3.063870 87 87 7.047985 14.095969
#> 764 0.008046923 3.063870 87 87 7.047985 14.095969
#> 765 0.008046923 3.063870 87 87 7.047985 14.095969
#> 766 0.008046923 3.063870 87 87 7.047985 14.095969
#> 767 0.008046923 3.063870 87 87 7.047985 14.095969
#> 768 0.008046923 3.063870 87 87 7.047985 14.095969
#> 769 0.008046923 3.063870 87 87 7.047985 12.404453
#> 770 0.007920229 3.035684 91 91 7.010820 14.021640
#> 771 0.007920229 3.035684 91 91 7.010820 14.021640
#> 772 0.007920229 3.035684 91 91 7.010820 14.021640
#> 773 0.007920229 3.035684 91 91 7.010820 14.021640
#> 774 0.007920229 3.035684 91 91 7.010820 84.129841
#> 775 0.007920229 3.035684 91 91 7.010820 14.021640
#> 776 0.007920229 3.035684 91 91 7.010820 14.021640
#> 777 0.007920229 3.035684 91 91 7.010820 14.021640
#> 778 0.007920229 3.035684 91 91 7.010820 14.505145
#> 779 0.007693063 3.064660 88 88 7.002909 14.005819
#> 780 0.007693063 3.064660 88 88 7.002909 14.005819
#> 781 0.008945098 3.008082 91 91 6.991053 13.982105
#> 782 0.008945098 3.008082 91 91 6.991053 13.982105
#> 783 0.008945098 3.008082 91 91 6.991053 13.982105
#> 784 0.009197813 2.994628 92 92 6.990339 13.980679
#> 785 0.009197813 2.994628 92 92 6.990339 41.942037
#> 786 0.009197813 2.994628 92 92 6.990339 13.980679
#> 787 0.009197813 2.994628 92 92 6.990339 13.980679
#> 788 0.009208543 3.001584 91 91 6.989041 13.978082
#> 789 0.009208543 3.001584 91 91 6.989041 13.978082
#> 790 0.007345618 3.082202 87 87 6.982620 6.982620
#> 791 0.007345618 3.082202 87 87 6.982620 13.965241
#> 792 0.007345618 3.082202 87 87 6.982620 13.965241
#> 793 0.007345618 3.082202 87 87 6.982620 41.895722
#> 794 0.007345618 3.082202 87 87 6.982620 13.965241
#> 795 0.006436894 3.144784 83 83 6.978502 6.978502
#> 796 0.006436894 3.144784 83 83 6.978502 6.978502
#> 797 0.006436894 3.144784 83 83 6.978502 20.935507
#> 798 0.006436894 3.144784 83 83 6.978502 6.978502
#> 799 0.006436894 3.144784 83 83 6.978502 13.957005
#> 800 0.006436894 3.144784 83 83 6.978502 13.957005
#> 801 0.006436894 3.144784 83 83 6.978502 13.957005
#> 802 0.006830676 3.097913 87 87 6.965067 13.930134
#> 803 0.006830676 3.097913 87 87 6.965067 13.930134
#> 804 0.006830676 3.097913 87 87 6.965067 6.965067
#> 805 0.006830676 3.097913 87 87 6.965067 13.930134
#> 806 0.006830676 3.097913 87 87 6.965067 13.930134
#> 807 0.006830676 3.097913 87 87 6.965067 55.720535
#> 808 0.006830676 3.097913 87 87 6.965067 13.930134
#> 809 0.007017543 3.107987 85 85 6.962961 6.962961
#> 810 0.007017543 3.107987 85 85 6.962961 6.962961
#> 811 0.007017543 3.107987 85 85 6.962961 6.962961
#> 812 0.007017543 3.107987 85 85 6.962961 6.962961
#> 813 0.008753122 3.011747 91 91 6.955059 13.910118
#> 814 0.008753122 3.011747 91 91 6.955059 13.910118
#> 815 0.007444717 3.070310 88 88 6.950438 13.900877
#> 816 0.007444717 3.070310 88 88 6.950438 13.452462
#> 817 0.007444717 3.070310 88 88 6.950438 13.900877
#> 818 0.007444717 3.070310 88 88 6.950438 13.900877
#> 819 0.007719673 3.039423 91 91 6.949522 13.899044
#> 820 0.007991791 3.046753 89 89 6.949498 13.898996
#> 821 0.007243730 3.076256 88 88 6.945250 13.890500
#> 822 0.007243730 3.076256 88 88 6.945250 13.890500
#> 823 0.007243730 3.076256 88 88 6.945250 13.890500
#> 824 0.007243730 3.076256 88 88 6.945250 13.890500
#> 825 0.007243730 3.076256 88 88 6.945250 13.890500
#> 826 0.008339286 3.052078 87 87 6.929367 6.929367
#> 827 0.008339286 3.052078 87 87 6.929367 18.016354
#> 828 0.008339286 3.052078 87 87 6.929367 6.929367
#> 829 0.008339286 3.052078 87 87 6.929367 13.858734
#> 830 0.008339286 3.052078 87 87 6.929367 13.858734
#> 831 0.008339286 3.052078 87 87 6.929367 13.858734
#> 832 0.008339286 3.052078 87 87 6.929367 13.858734
#> 833 0.008339286 3.052078 87 87 6.929367 13.858734
#> 834 0.008377248 3.027632 90 90 6.915567 27.662268
#> 835 0.007746254 3.044723 90 90 6.905874 13.811747
#> 836 0.007746254 3.044723 90 90 6.905874 13.811747
#> 837 0.007746254 3.044723 90 90 6.905874 13.811747
#> 838 0.007746254 3.044723 90 90 6.905874 13.811747
#> 839 0.007746254 3.044723 90 90 6.905874 13.811747
#> 840 0.007746254 3.044723 90 90 6.905874 13.811747
#> 841 0.007746254 3.044723 90 90 6.905874 13.811747
#> 842 0.007746254 3.044723 90 90 6.905874 13.811747
#> 843 0.007746254 3.044723 90 90 6.905874 13.811747
#> 844 0.007303857 3.095567 85 85 6.858019 6.858019
#> 845 0.007303857 3.095567 85 85 6.858019 6.974256
#> 846 0.007303857 3.095567 85 85 6.858019 13.716037
#> 847 0.007303857 3.095567 85 85 6.858019 13.716037
#> 848 0.007303857 3.095567 85 85 6.858019 13.716037
#> 849 0.007554303 3.071838 87 87 6.856204 13.712407
#> 850 0.007554303 3.071838 87 87 6.856204 13.712407
#> 851 0.008367352 3.055881 86 86 6.826298 6.826298
#> 852 0.008367352 3.055881 86 86 6.826298 6.826298
#> 853 0.008367352 3.055881 86 86 6.826298 13.652596
#> 854 0.008367352 3.055881 86 86 6.826298 13.652596
#> 855 0.008367352 3.055881 86 86 6.826298 13.652596
#> 856 0.008367352 3.055881 86 86 6.826298 13.652596
#> 857 0.007917341 3.037179 90 90 6.822802 13.205423
#> 858 0.007917341 3.037179 90 90 6.822802 40.936812
#> 859 0.007917341 3.037179 90 90 6.822802 13.645604
#> 860 0.007917341 3.037179 90 90 6.822802 13.645604
#> 861 0.007917341 3.037179 90 90 6.822802 13.645604
#> 862 0.006985661 3.112176 84 84 6.806172 6.806172
#> 863 0.006985661 3.112176 84 84 6.806172 13.612345
#> 864 0.008046923 3.063870 86 86 6.802708 6.802708
#> 865 0.008046923 3.063870 86 86 6.802708 13.605417
#> 866 0.008046923 3.063870 86 86 6.802708 13.605417
#> 867 0.008046923 3.063870 86 86 6.802708 6.802708
#> 868 0.008046923 3.063870 86 86 6.802708 13.605417
#> 869 0.008046923 3.063870 86 86 6.802708 27.210834
#> 870 0.007920229 3.035684 90 90 6.779551 13.559102
#> 871 0.007920229 3.035684 90 90 6.779551 13.559102
#> 872 0.007920229 3.035684 90 90 6.779551 13.559102
#> 873 0.007920229 3.035684 90 90 6.779551 13.121712
#> 874 0.007920229 3.035684 90 90 6.779551 13.559102
#> 875 0.009197813 2.994628 91 91 6.765260 16.236623
#> 876 0.009197813 2.994628 91 91 6.765260 13.530519
#> 877 0.009197813 2.994628 91 91 6.765260 13.530519
#> 878 0.009197813 2.994628 91 91 6.765260 13.530519
#> 879 0.008945098 3.008082 90 90 6.762498 13.524996
#> 880 0.008945098 3.008082 90 90 6.762498 13.524996
#> 881 0.008945098 3.008082 90 90 6.762498 13.524996
#> 882 0.008945098 3.008082 90 90 6.762498 13.524996
#> 883 0.007693063 3.064660 87 87 6.761878 13.523755
#> 884 0.009208543 3.001584 90 90 6.761038 13.522075
#> 885 0.009208543 3.001584 90 90 6.761038 13.522075
#> 886 0.007345618 3.082202 86 86 6.738191 13.476381
#> 887 0.007345618 3.082202 86 86 6.738191 13.476381
#> 888 0.007345618 3.082202 86 86 6.738191 6.738191
#> 889 0.007345618 3.082202 86 86 6.738191 13.476381
#> 890 0.007345618 3.082202 86 86 6.738191 13.476381
#> 891 0.006830676 3.097913 86 86 6.720031 13.440062
#> 892 0.006830676 3.097913 86 86 6.720031 6.720031
#> 893 0.006830676 3.097913 86 86 6.720031 13.440062
#> 894 0.006830676 3.097913 86 86 6.720031 13.440062
#> 895 0.006830676 3.097913 86 86 6.720031 13.440062
#> 896 0.006830676 3.097913 86 86 6.720031 13.440062
#> 897 0.006830676 3.097913 86 86 6.720031 13.440062
#> 898 0.006436894 3.144784 82 82 6.717495 6.717495
#> 899 0.006436894 3.144784 82 82 6.717495 6.717495
#> 900 0.006436894 3.144784 82 82 6.717495 6.717495
#> 901 0.006436894 3.144784 82 82 6.717495 6.717495
#> 902 0.006436894 3.144784 82 82 6.717495 6.717495
#> 903 0.006436894 3.144784 82 82 6.717495 13.434989
#> 904 0.006436894 3.144784 82 82 6.717495 13.434989
#> 905 0.006436894 3.144784 82 82 6.717495 13.434989
#> 906 0.006436894 3.144784 82 82 6.717495 13.434989
#> 907 0.007017543 3.107987 84 84 6.711506 6.711506
#> 908 0.007017543 3.107987 84 84 6.711506 6.711506
#> 909 0.007017543 3.107987 84 84 6.711506 6.711506
#> 910 0.007444717 3.070310 87 87 6.710779 13.421559
#> 911 0.007444717 3.070310 87 87 6.710779 13.421559
#> 912 0.007243730 3.076256 87 87 6.705314 13.410629
#> 913 0.007243730 3.076256 87 87 6.705314 13.410629
#> 914 0.007243730 3.076256 87 87 6.705314 13.410629
#> 915 0.008339286 3.052078 86 86 6.689131 6.689131
#> 916 0.008339286 3.052078 86 86 6.689131 6.689131
#> 917 0.008339286 3.052078 86 86 6.689131 13.378262
#> 918 0.008339286 3.052078 86 86 6.689131 13.378262
#> 919 0.008339286 3.052078 86 86 6.689131 26.756523
#> 920 0.008339286 3.052078 86 86 6.689131 13.378262
#> 921 0.008377248 3.027632 89 89 6.685536 13.371071
#> 922 0.008377248 3.027632 89 89 6.685536 20.056607
#> 923 0.008377248 3.027632 89 89 6.685536 13.371071
#> 924 0.008377248 3.027632 89 89 6.685536 13.371071
#> 925 0.008377248 3.027632 89 89 6.685536 13.371071
#> 926 0.008377248 3.027632 89 89 6.685536 13.371071
#> 927 0.007746254 3.044723 89 89 6.674890 13.349780
#> 928 0.007746254 3.044723 89 89 6.674890 13.349780
#> 929 0.007746254 3.044723 89 89 6.674890 66.748898
#> 930 0.007746254 3.044723 89 89 6.674890 13.349780
#> 931 0.007746254 3.044723 89 89 6.674890 13.349780
#> 932 0.007746254 3.044723 89 89 6.674890 13.349780
#> 933 0.007746254 3.044723 89 89 6.674890 13.349780
#> 934 0.007746254 3.044723 89 89 6.674890 13.349780
#> 935 0.007746254 3.044723 89 89 6.674890 13.349780
#> 936 0.007554303 3.071838 86 86 6.616992 6.616992
#> 937 0.007554303 3.071838 86 86 6.616992 13.233984
#> 938 0.007554303 3.071838 86 86 6.616992 13.233984
#> 939 0.007303857 3.095567 84 84 6.611326 6.611326
#> 940 0.007303857 3.095567 84 84 6.611326 6.611326
#> 941 0.007303857 3.095567 84 84 6.611326 6.611326
#> 942 0.007303857 3.095567 84 84 6.611326 13.222652
#> 943 0.007303857 3.095567 84 84 6.611326 13.222652
#> 944 0.007917341 3.037179 89 89 6.595153 13.190305
#> 945 0.007917341 3.037179 89 89 6.595153 13.190305
#> 946 0.008367352 3.055881 85 85 6.586623 6.586623
#> 947 0.008367352 3.055881 85 85 6.586623 13.173246
#> 948 0.008367352 3.055881 85 85 6.586623 19.759869
#> 949 0.008367352 3.055881 85 85 6.586623 13.173246
#> 950 0.008367352 3.055881 85 85 6.586623 13.173246
#> 951 0.008367352 3.055881 85 85 6.586623 13.173246
#> 952 0.008046923 3.063870 85 85 6.563249 13.126497
#> 953 0.008046923 3.063870 85 85 6.563249 6.563249
#> 954 0.008046923 3.063870 85 85 6.563249 6.563249
#> 955 0.008046923 3.063870 85 85 6.563249 13.126497
#> 956 0.008046923 3.063870 85 85 6.563249 13.126497
#> 957 0.006985661 3.112176 83 83 6.557162 13.114324
#> 958 0.006985661 3.112176 83 83 6.557162 6.557162
#> 959 0.006985661 3.112176 83 83 6.557162 6.557162
#> 960 0.006985661 3.112176 83 83 6.557162 6.557162
#> 961 0.006985661 3.112176 83 83 6.557162 6.557162
#> 962 0.007920229 3.035684 89 89 6.553454 13.106908
#> 963 0.007920229 3.035684 89 89 6.553454 13.106908
#> 964 0.007920229 3.035684 89 89 6.553454 13.106908
#> 965 0.007920229 3.035684 89 89 6.553454 19.660362
#> 966 0.007920229 3.035684 89 89 6.553454 104.855266
#> 967 0.007920229 3.035684 89 89 6.553454 13.106908
#> 968 0.007920229 3.035684 89 89 6.553454 12.684105
#> 969 0.007920229 3.035684 89 89 6.553454 26.213817
#> 970 0.007920229 3.035684 89 89 6.553454 13.106908
#> 971 0.007920229 3.035684 89 89 6.553454 19.660362
#> 972 0.009197813 2.994628 90 90 6.545059 85.085772
#> 973 0.009197813 2.994628 90 90 6.545059 19.635178
#> 974 0.009197813 2.994628 90 90 6.545059 6.545059
#> 975 0.009197813 2.994628 90 90 6.545059 13.090119
#> 976 0.009197813 2.994628 90 90 6.545059 26.180238
#> 977 0.009197813 2.994628 90 90 6.545059 26.180238
#> 978 0.009197813 2.994628 90 90 6.545059 13.090119
#> 979 0.008945098 3.008082 89 89 6.538986 13.077972
#> 980 0.008945098 3.008082 89 89 6.538986 13.077972
#> 981 0.008945098 3.008082 89 89 6.538986 13.077972
#> 982 0.008945098 3.008082 89 89 6.538986 13.077972
#> 983 0.009208543 3.001584 89 89 6.538049 13.076097
#> 984 0.007693063 3.064660 86 86 6.526499 13.052997
#> 985 0.007693063 3.064660 86 86 6.526499 13.052997
#> 986 0.007693063 3.064660 86 86 6.526499 13.052997
#> 987 0.007693063 3.064660 86 86 6.526499 12.631933
#> 988 0.007693063 3.064660 86 86 6.526499 13.052997
#> 989 0.008753122 3.011747 89 89 6.504790 12.589916
#> 990 0.007345618 3.082202 85 85 6.499608 25.998433
#> 991 0.007719673 3.039423 89 89 6.495615 38.973691
#> 992 0.007719673 3.039423 89 89 6.495615 51.964921
#> 993 0.007991791 3.046753 87 87 6.484548 12.969095
#> 994 0.007991791 3.046753 87 87 6.484548 12.969095
#> 995 0.007991791 3.046753 87 87 6.484548 12.969095
#> 996 0.007991791 3.046753 87 87 6.484548 12.550737
#> 997 0.006830676 3.097913 85 85 6.480901 12.961801
#> 998 0.006830676 3.097913 85 85 6.480901 12.961801
#> 999 0.006830676 3.097913 85 85 6.480901 6.480901
#> 1000 0.006830676 3.097913 85 85 6.480901 12.961801
#> 1001 0.006830676 3.097913 85 85 6.480901 12.961801
#> 1002 0.007444717 3.070310 86 86 6.476756 12.953513
#> 1003 0.007444717 3.070310 86 86 6.476756 12.953513
#> 1004 0.007444717 3.070310 86 86 6.476756 12.535657
#> 1005 0.007444717 3.070310 86 86 6.476756 12.953513
#> 1006 0.007243730 3.076256 86 86 6.471037 12.942074
#> 1007 0.007243730 3.076256 86 86 6.471037 19.413111
#> 1008 0.007243730 3.076256 86 86 6.471037 12.942074
#> 1009 0.007017543 3.107987 83 83 6.466284 6.466284
#> 1010 0.007017543 3.107987 83 83 6.466284 6.466284
#> 1011 0.007017543 3.107987 83 83 6.466284 6.466284
#> 1012 0.007017543 3.107987 83 83 6.466284 6.466284
#> 1013 0.007017543 3.107987 83 83 6.466284 6.466284
#> 1014 0.007017543 3.107987 83 83 6.466284 12.932568
#> 1015 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1016 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1017 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1018 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1019 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1020 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1021 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1022 0.006436894 3.144784 81 81 6.463225 6.463225
#> 1023 0.008377248 3.027632 88 88 6.460686 12.921371
#> 1024 0.008377248 3.027632 88 88 6.460686 12.921371
#> 1025 0.008377248 3.027632 88 88 6.460686 12.921371
#> 1026 0.008377248 3.027632 88 88 6.460686 12.921371
#> 1027 0.008377248 3.027632 88 88 6.460686 12.921371
#> 1028 0.007746254 3.044723 88 88 6.449152 12.898304
#> 1029 0.007746254 3.044723 88 88 6.449152 12.898304
#> 1030 0.007746254 3.044723 88 88 6.449152 12.482230
#> 1031 0.007746254 3.044723 88 88 6.449152 12.898304
#> 1032 0.007746254 3.044723 88 88 6.449152 12.482230
#> 1033 0.007554303 3.071838 85 85 6.383475 12.766949
#> 1034 0.007554303 3.071838 85 85 6.383475 12.766949
#> 1035 0.007554303 3.071838 85 85 6.383475 12.766949
#> 1036 0.007917341 3.037179 88 88 6.372655 12.745310
#> 1037 0.007917341 3.037179 88 88 6.372655 12.745310
#> 1038 0.007917341 3.037179 88 88 6.372655 12.745310
#> 1039 0.007303857 3.095567 83 83 6.370711 12.741422
#> 1040 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1041 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1042 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1043 0.007303857 3.095567 83 83 6.370711 12.741422
#> 1044 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1045 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1046 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1047 0.007303857 3.095567 83 83 6.370711 6.370711
#> 1048 0.007303857 3.095567 83 83 6.370711 12.741422
#> 1049 0.008367352 3.055881 84 84 6.352676 6.352676
#> 1050 0.008367352 3.055881 84 84 6.352676 6.352676
#> 1051 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1052 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1053 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1054 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1055 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1056 0.008367352 3.055881 84 84 6.352676 12.705351
#> 1057 0.007920229 3.035684 88 88 6.332470 12.664940
#> 1058 0.007920229 3.035684 88 88 6.332470 12.664940
#> 1059 0.007920229 3.035684 88 88 6.332470 101.319521
#> 1060 0.007920229 3.035684 88 88 6.332470 12.664940
#> 1061 0.007920229 3.035684 88 88 6.332470 13.101662
#> 1062 0.009197813 2.994628 89 89 6.329686 12.659372
#> 1063 0.009197813 2.994628 89 89 6.329686 12.659372
#> 1064 0.009197813 2.994628 89 89 6.329686 12.659372
#> 1065 0.009197813 2.994628 89 89 6.329686 12.659372
#> 1066 0.009197813 2.994628 89 89 6.329686 69.626544
#> 1067 0.008046923 3.063870 84 84 6.329533 6.329533
#> 1068 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1069 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1070 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1071 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1072 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1073 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1074 0.008046923 3.063870 84 84 6.329533 12.659066
#> 1075 0.008945098 3.008082 88 88 6.320461 12.640922
#> 1076 0.008945098 3.008082 88 88 6.320461 12.640922
#> 1077 0.008945098 3.008082 88 88 6.320461 37.922765
#> 1078 0.009208543 3.001584 88 88 6.320019 12.640038
#> 1079 0.009208543 3.001584 88 88 6.320019 12.640038
#> 1080 0.009208543 3.001584 88 88 6.320019 12.640038
#> 1081 0.009208543 3.001584 88 88 6.320019 12.640038
#> 1082 0.009208543 3.001584 88 88 6.320019 12.640038
#> 1083 0.006985661 3.112176 82 82 6.314409 12.628817
#> 1084 0.006985661 3.112176 82 82 6.314409 12.628817
#> 1085 0.006985661 3.112176 82 82 6.314409 6.314409
#> 1086 0.006985661 3.112176 82 82 6.314409 18.943226
#> 1087 0.007693063 3.064660 85 85 6.296703 12.593407
#> 1088 0.008753122 3.011747 88 88 6.287147 12.574294
#> 1089 0.008753122 3.011747 88 88 6.287147 12.574294
#> 1090 0.007719673 3.039423 88 88 6.276316 12.552633
#> 1091 0.007345618 3.082202 84 84 6.266799 6.266799
#> 1092 0.007345618 3.082202 84 84 6.266799 12.533598
#> 1093 0.007345618 3.082202 84 84 6.266799 12.533598
#> 1094 0.007345618 3.082202 84 84 6.266799 12.533598
#> 1095 0.007345618 3.082202 84 84 6.266799 12.533598
#> 1096 0.007345618 3.082202 84 84 6.266799 12.533598
#> 1097 0.007345618 3.082202 84 84 6.266799 18.800397
#> 1098 0.007991791 3.046753 86 86 6.260118 12.520237
#> 1099 0.007444717 3.070310 85 85 6.248299 12.496599
#> 1100 0.007444717 3.070310 85 85 6.248299 12.496599
#> 1101 0.007444717 3.070310 85 85 6.248299 12.496599
#> 1102 0.007444717 3.070310 85 85 6.248299 18.744898
#> 1103 0.007444717 3.070310 85 85 6.248299 12.496599
#> 1104 0.006830676 3.097913 84 84 6.247600 6.353491
#> 1105 0.006830676 3.097913 84 84 6.247600 12.495200
#> 1106 0.006830676 3.097913 84 84 6.247600 6.247600
#> 1107 0.006830676 3.097913 84 84 6.247600 12.495200
#> 1108 0.007243730 3.076256 85 85 6.242348 12.484696
#> 1109 0.007243730 3.076256 85 85 6.242348 26.779672
#> 1110 0.007243730 3.076256 85 85 6.242348 12.484696
#> 1111 0.008377248 3.027632 87 87 6.240957 12.481914
#> 1112 0.008377248 3.027632 87 87 6.240957 12.481914
#> 1113 0.007746254 3.044723 87 87 6.228599 12.457199
#> 1114 0.007746254 3.044723 87 87 6.228599 12.457199
#> 1115 0.007746254 3.044723 87 87 6.228599 12.457199
#> 1116 0.007017543 3.107987 82 82 6.227211 6.227211
#> 1117 0.007017543 3.107987 82 82 6.227211 6.227211
#> 1118 0.007017543 3.107987 82 82 6.227211 6.227211
#> 1119 0.007017543 3.107987 82 82 6.227211 6.227211
#> 1120 0.008339286 3.052078 84 84 6.225583 12.451165
#> 1121 0.008339286 3.052078 84 84 6.225583 12.451165
#> 1122 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1123 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1124 0.006436894 3.144784 80 80 6.215600 12.431201
#> 1125 0.006436894 3.144784 80 80 6.215600 12.431201
#> 1126 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1127 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1128 0.006436894 3.144784 80 80 6.215600 12.431201
#> 1129 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1130 0.006436894 3.144784 80 80 6.215600 24.862402
#> 1131 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1132 0.006436894 3.144784 80 80 6.215600 12.431201
#> 1133 0.006436894 3.144784 80 80 6.215600 6.215600
#> 1134 0.006436894 3.144784 80 80 6.215600 12.431201
#> 1135 0.007554303 3.071838 84 84 6.155580 6.155580
#> 1136 0.007554303 3.071838 84 84 6.155580 6.155580
#> 1137 0.007554303 3.071838 84 84 6.155580 12.311161
#> 1138 0.007554303 3.071838 84 84 6.155580 12.311161
#> 1139 0.007554303 3.071838 84 84 6.155580 12.311161
#> 1140 0.007917341 3.037179 87 87 6.155249 12.310497
#> 1141 0.007917341 3.037179 87 87 6.155249 12.310497
#> 1142 0.007303857 3.095567 82 82 6.136095 6.136095
#> 1143 0.007303857 3.095567 82 82 6.136095 6.136095
#> 1144 0.007303857 3.095567 82 82 6.136095 6.136095
#> 1145 0.007303857 3.095567 82 82 6.136095 12.272191
#> 1146 0.007303857 3.095567 82 82 6.136095 12.272191
#> 1147 0.008367352 3.055881 83 83 6.124384 6.124384
#> 1148 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1149 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1150 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1151 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1152 0.008367352 3.055881 83 83 6.124384 18.373153
#> 1153 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1154 0.008367352 3.055881 83 83 6.124384 12.248769
#> 1155 0.009197813 2.994628 88 88 6.119085 12.238171
#> 1156 0.009197813 2.994628 88 88 6.119085 12.238171
#> 1157 0.009197813 2.994628 88 88 6.119085 11.843391
#> 1158 0.009197813 2.994628 88 88 6.119085 12.238171
#> 1159 0.009197813 2.994628 88 88 6.119085 12.660177
#> 1160 0.009197813 2.994628 88 88 6.119085 24.476341
#> 1161 0.009197813 2.994628 88 88 6.119085 30.595427
#> 1162 0.007920229 3.035684 87 87 6.116539 12.233079
#> 1163 0.007920229 3.035684 87 87 6.116539 24.466157
#> 1164 0.007920229 3.035684 87 87 6.116539 24.466157
#> 1165 0.009208543 3.001584 87 87 6.106892 12.213785
#> 1166 0.009208543 3.001584 87 87 6.106892 12.213785
#> 1167 0.008945098 3.008082 87 87 6.106866 25.269789
#> 1168 0.008945098 3.008082 87 87 6.106866 12.213732
#> 1169 0.008945098 3.008082 87 87 6.106866 12.213732
#> 1170 0.008046923 3.063870 83 83 6.101490 12.202979
#> 1171 0.008046923 3.063870 83 83 6.101490 6.101490
#> 1172 0.008046923 3.063870 83 83 6.101490 12.202979
#> 1173 0.008046923 3.063870 83 83 6.101490 10.738622
#> 1174 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1175 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1176 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1177 0.006985661 3.112176 81 81 6.077828 12.155656
#> 1178 0.006985661 3.112176 81 81 6.077828 12.155656
#> 1179 0.006985661 3.112176 81 81 6.077828 12.155656
#> 1180 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1181 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1182 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1183 0.006985661 3.112176 81 81 6.077828 6.077828
#> 1184 0.008753122 3.011747 87 87 6.074423 12.148847
#> 1185 0.007693063 3.064660 84 84 6.072423 12.144845
#> 1186 0.007693063 3.064660 84 84 6.072423 12.144845
#> 1187 0.007693063 3.064660 84 84 6.072423 12.144845
#> 1188 0.007693063 3.064660 84 84 6.072423 11.040768
#> 1189 0.007719673 3.039423 87 87 6.062041 11.732983
#> 1190 0.007719673 3.039423 87 87 6.062041 12.124082
#> 1191 0.007991791 3.046753 85 85 6.040967 12.081934
#> 1192 0.007991791 3.046753 85 85 6.040967 12.081934
#> 1193 0.007991791 3.046753 85 85 6.040967 11.692195
#> 1194 0.007991791 3.046753 85 85 6.040967 12.081934
#> 1195 0.007991791 3.046753 85 85 6.040967 12.081934
#> 1196 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1197 0.007345618 3.082202 83 83 6.039690 6.039690
#> 1198 0.007345618 3.082202 83 83 6.039690 6.142058
#> 1199 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1200 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1201 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1202 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1203 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1204 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1205 0.007345618 3.082202 83 83 6.039690 12.079380
#> 1206 0.008377248 3.027632 86 86 6.026290 12.052581
#> 1207 0.008377248 3.027632 86 86 6.026290 12.052581
#> 1208 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1209 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1210 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1211 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1212 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1213 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1214 0.007444717 3.070310 84 84 6.025340 12.050680
#> 1215 0.006830676 3.097913 83 83 6.020054 6.020054
#> 1216 0.006830676 3.097913 83 83 6.020054 12.040107
#> 1217 0.007243730 3.076256 84 84 6.019177 12.038354
#> 1218 0.007243730 3.076256 84 84 6.019177 12.038354
#> 1219 0.007243730 3.076256 84 84 6.019177 12.038354
#> 1220 0.007243730 3.076256 84 84 6.019177 12.038354
#> 1221 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1222 0.007746254 3.044723 86 86 6.013169 23.276785
#> 1223 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1224 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1225 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1226 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1227 0.007746254 3.044723 86 86 6.013169 12.026339
#> 1228 0.008339286 3.052078 83 83 6.002132 6.002132
#> 1229 0.008339286 3.052078 83 83 6.002132 12.004264
#> 1230 0.008339286 3.052078 83 83 6.002132 12.004264
#> 1231 0.008339286 3.052078 83 83 6.002132 12.004264
#> 1232 0.008339286 3.052078 83 83 6.002132 12.004264
#> 1233 0.008339286 3.052078 83 83 6.002132 12.004264
#> 1234 0.007017543 3.107987 81 81 5.994206 5.994206
#> 1235 0.007017543 3.107987 81 81 5.994206 5.994206
#> 1236 0.007017543 3.107987 81 81 5.994206 5.994206
#> 1237 0.007017543 3.107987 81 81 5.994206 5.994206
#> 1238 0.007017543 3.107987 81 81 5.994206 5.994206
#> 1239 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1240 0.006436894 3.144784 79 79 5.974526 11.949052
#> 1241 0.006436894 3.144784 79 79 5.974526 17.923578
#> 1242 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1243 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1244 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1245 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1246 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1247 0.006436894 3.144784 79 79 5.974526 5.974526
#> 1248 0.006436894 3.144784 79 79 5.974526 11.949052
#> 1249 0.006436894 3.144784 79 79 5.974526 11.949052
#> 1250 0.006436894 3.144784 79 79 5.974526 11.949052
#> 1251 0.007917341 3.037179 86 86 5.942874 11.885748
#> 1252 0.007917341 3.037179 86 86 5.942874 11.885748
#> 1253 0.007917341 3.037179 86 86 5.942874 11.885748
#> 1254 0.007917341 3.037179 86 86 5.942874 11.885748
#> 1255 0.007917341 3.037179 86 86 5.942874 11.885748
#> 1256 0.007554303 3.071838 83 83 5.933238 5.741843
#> 1257 0.007554303 3.071838 83 83 5.933238 11.866476
#> 1258 0.007554303 3.071838 83 83 5.933238 11.866476
#> 1259 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1260 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1261 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1262 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1263 0.009197813 2.994628 87 87 5.913205 35.479229
#> 1264 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1265 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1266 0.009197813 2.994628 87 87 5.913205 11.826410
#> 1267 0.009197813 2.994628 87 87 5.913205 23.652819
#> 1268 0.007303857 3.095567 81 81 5.907399 11.814799
#> 1269 0.007303857 3.095567 81 81 5.907399 11.814799
#> 1270 0.007303857 3.095567 81 81 5.907399 5.907399
#> 1271 0.007303857 3.095567 81 81 5.907399 11.814799
#> 1272 0.007303857 3.095567 81 81 5.907399 23.629598
#> 1273 0.007303857 3.095567 81 81 5.907399 11.814799
#> 1274 0.007920229 3.035684 86 86 5.905602 11.811205
#> 1275 0.007920229 3.035684 86 86 5.905602 11.811205
#> 1276 0.007920229 3.035684 86 86 5.905602 11.811205
#> 1277 0.007920229 3.035684 86 86 5.905602 11.430198
#> 1278 0.007920229 3.035684 86 86 5.905602 17.716807
#> 1279 0.007920229 3.035684 86 86 5.905602 11.811205
#> 1280 0.007920229 3.035684 86 86 5.905602 11.430198
#> 1281 0.007920229 3.035684 86 86 5.905602 11.430198
#> 1282 0.007920229 3.035684 86 86 5.905602 11.811205
#> 1283 0.008367352 3.055881 82 82 5.901679 5.901679
#> 1284 0.008367352 3.055881 82 82 5.901679 5.901679
#> 1285 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1286 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1287 0.008367352 3.055881 82 82 5.901679 5.901679
#> 1288 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1289 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1290 0.008367352 3.055881 82 82 5.901679 17.705036
#> 1291 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1292 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1293 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1294 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1295 0.008367352 3.055881 82 82 5.901679 11.803357
#> 1296 0.009208543 3.001584 86 86 5.898613 11.797226
#> 1297 0.009208543 3.001584 86 86 5.898613 11.797226
#> 1298 0.009208543 3.001584 86 86 5.898613 11.797226
#> 1299 0.009208543 3.001584 86 86 5.898613 11.416670
#> 1300 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1301 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1302 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1303 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1304 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1305 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1306 0.008945098 3.008082 86 86 5.898144 11.796289
#> 1307 0.008046923 3.063870 82 82 5.879047 23.516188
#> 1308 0.008046923 3.063870 82 82 5.879047 5.879047
#> 1309 0.008046923 3.063870 82 82 5.879047 11.758094
#> 1310 0.008046923 3.063870 82 82 5.879047 11.758094
#> 1311 0.008046923 3.063870 82 82 5.879047 11.758094
#> 1312 0.008046923 3.063870 82 82 5.879047 5.879047
#> 1313 0.008046923 3.063870 82 82 5.879047 11.758094
#> 1314 0.008046923 3.063870 82 82 5.879047 5.879047
#> 1315 0.008753122 3.011747 86 86 5.866562 11.733124
#> 1316 0.007693063 3.064660 83 83 5.853587 11.707174
#> 1317 0.007693063 3.064660 83 83 5.853587 11.707174
#> 1318 0.007693063 3.064660 83 83 5.853587 12.110870
#> 1319 0.006985661 3.112176 80 80 5.847337 5.847337
#> 1320 0.006985661 3.112176 80 80 5.847337 11.694674
#> 1321 0.006985661 3.112176 80 80 5.847337 11.694674
#> 1322 0.006985661 3.112176 80 80 5.847337 5.847337
#> 1323 0.006985661 3.112176 80 80 5.847337 5.847337
#> 1324 0.007991791 3.046753 84 84 5.827030 11.654060
#> 1325 0.007345618 3.082202 82 82 5.818207 5.818207
#> 1326 0.007345618 3.082202 82 82 5.818207 5.916821
#> 1327 0.007345618 3.082202 82 82 5.818207 5.818207
#> 1328 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1329 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1330 0.007345618 3.082202 82 82 5.818207 23.272829
#> 1331 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1332 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1333 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1334 0.007345618 3.082202 82 82 5.818207 11.636415
#> 1335 0.008377248 3.027632 85 85 5.816626 11.633252
#> 1336 0.008377248 3.027632 85 85 5.816626 17.449878
#> 1337 0.007444717 3.070310 83 83 5.807808 11.615617
#> 1338 0.007444717 3.070310 83 83 5.807808 11.615617
#> 1339 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1340 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1341 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1342 0.007746254 3.044723 85 85 5.802801 17.408404
#> 1343 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1344 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1345 0.007746254 3.044723 85 85 5.802801 11.605602
#> 1346 0.007243730 3.076256 83 83 5.801455 11.602910
#> 1347 0.007243730 3.076256 83 83 5.801455 11.602910
#> 1348 0.007243730 3.076256 83 83 5.801455 11.602910
#> 1349 0.006830676 3.097913 82 82 5.798187 5.798187
#> 1350 0.006830676 3.097913 82 82 5.798187 5.798187
#> 1351 0.006830676 3.097913 82 82 5.798187 11.596373
#> 1352 0.006830676 3.097913 82 82 5.798187 11.596373
#> 1353 0.006830676 3.097913 82 82 5.798187 5.798187
#> 1354 0.006830676 3.097913 82 82 5.798187 11.596373
#> 1355 0.006830676 3.097913 82 82 5.798187 23.192747
#> 1356 0.006830676 3.097913 82 82 5.798187 11.596373
#> 1357 0.008339286 3.052078 82 82 5.784138 11.568277
#> 1358 0.008339286 3.052078 82 82 5.784138 5.784138
#> 1359 0.008339286 3.052078 82 82 5.784138 5.784138
#> 1360 0.008339286 3.052078 82 82 5.784138 11.568277
#> 1361 0.008339286 3.052078 82 82 5.784138 11.568277
#> 1362 0.008339286 3.052078 82 82 5.784138 11.568277
#> 1363 0.007017543 3.107987 80 80 5.767186 5.767186
#> 1364 0.007017543 3.107987 80 80 5.767186 5.767186
#> 1365 0.007017543 3.107987 80 80 5.767186 5.767186
#> 1366 0.007017543 3.107987 80 80 5.767186 5.767186
#> 1367 0.007017543 3.107987 80 80 5.767186 5.767186
#> 1368 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1369 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1370 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1371 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1372 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1373 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1374 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1375 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1376 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1377 0.006436894 3.144784 78 78 5.739909 5.739909
#> 1378 0.006436894 3.144784 78 78 5.739909 11.479817
#> 1379 0.006436894 3.144784 78 78 5.739909 11.479817
#> 1380 0.007917341 3.037179 85 85 5.735471 11.470942
#> 1381 0.007917341 3.037179 85 85 5.735471 11.100912
#> 1382 0.007917341 3.037179 85 85 5.735471 11.470942
#> 1383 0.007554303 3.071838 82 82 5.716377 11.432754
#> 1384 0.007554303 3.071838 82 82 5.716377 11.432754
#> 1385 0.007554303 3.071838 82 82 5.716377 11.432754
#> 1386 0.009197813 2.994628 86 86 5.711991 11.423981
#> 1387 0.009197813 2.994628 86 86 5.711991 11.423981
#> 1388 0.009197813 2.994628 86 86 5.711991 5.711991
#> 1389 0.009197813 2.994628 86 86 5.711991 11.423981
#> 1390 0.009197813 2.994628 86 86 5.711991 22.847962
#> 1391 0.009197813 2.994628 86 86 5.711991 22.847962
#> 1392 0.009197813 2.994628 86 86 5.711991 11.423981
#> 1393 0.009197813 2.994628 86 86 5.711991 11.423981
#> 1394 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1395 0.007920229 3.035684 85 85 5.699600 22.798399
#> 1396 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1397 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1398 0.007920229 3.035684 85 85 5.699600 17.098800
#> 1399 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1400 0.007920229 3.035684 85 85 5.699600 34.197599
#> 1401 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1402 0.007920229 3.035684 85 85 5.699600 17.098800
#> 1403 0.007920229 3.035684 85 85 5.699600 11.399200
#> 1404 0.009208543 3.001584 85 85 5.695125 11.390251
#> 1405 0.009208543 3.001584 85 85 5.695125 11.390251
#> 1406 0.009208543 3.001584 85 85 5.695125 11.390251
#> 1407 0.008945098 3.008082 85 85 5.694240 11.781186
#> 1408 0.008945098 3.008082 85 85 5.694240 22.776960
#> 1409 0.008945098 3.008082 85 85 5.694240 11.388480
#> 1410 0.008945098 3.008082 85 85 5.694240 11.388480
#> 1411 0.008945098 3.008082 85 85 5.694240 11.388480
#> 1412 0.009694289 2.982039 86 86 5.692016 11.384032
#> 1413 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1414 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1415 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1416 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1417 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1418 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1419 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1420 0.007303857 3.095567 80 80 5.684544 17.053633
#> 1421 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1422 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1423 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1424 0.007303857 3.095567 80 80 5.684544 11.369089
#> 1425 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1426 0.008367352 3.055881 81 81 5.684487 51.160383
#> 1427 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1428 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1429 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1430 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1431 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1432 0.008367352 3.055881 81 81 5.684487 22.737948
#> 1433 0.008367352 3.055881 81 81 5.684487 11.368974
#> 1434 0.008367352 3.055881 81 81 5.684487 13.642769
#> 1435 0.011033912 2.937112 88 88 5.674047 11.348094
#> 1436 0.008046923 3.063870 81 81 5.662133 11.324266
#> 1437 0.008046923 3.063870 81 81 5.662133 11.324266
#> 1438 0.008046923 3.063870 81 81 5.662133 11.324266
#> 1439 0.008046923 3.063870 81 81 5.662133 11.324266
#> 1440 0.008046923 3.063870 81 81 5.662133 11.324266
#> 1441 0.007693063 3.064660 82 82 5.640128 11.280257
#> 1442 0.007693063 3.064660 82 82 5.640128 12.069875
#> 1443 0.007693063 3.064660 82 82 5.640128 16.920385
#> 1444 0.007693063 3.064660 82 82 5.640128 11.280257
#> 1445 0.007693063 3.064660 82 82 5.640128 11.280257
#> 1446 0.007693063 3.064660 82 82 5.640128 11.280257
#> 1447 0.007693063 3.064660 82 82 5.640128 11.280257
#> 1448 0.006985661 3.112176 79 79 5.622852 5.622852
#> 1449 0.007991791 3.046753 83 83 5.618243 11.236486
#> 1450 0.007991791 3.046753 83 83 5.618243 11.236486
#> 1451 0.008377248 3.027632 84 84 5.611904 11.223807
#> 1452 0.008377248 3.027632 84 84 5.611904 10.861749
#> 1453 0.008377248 3.027632 84 84 5.611904 11.223807
#> 1454 0.008377248 3.027632 84 84 5.611904 11.223807
#> 1455 0.008377248 3.027632 84 84 5.611904 11.223807
#> 1456 0.008377248 3.027632 84 84 5.611904 11.223807
#> 1457 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1458 0.007345618 3.082202 81 81 5.602278 5.697232
#> 1459 0.007345618 3.082202 81 81 5.602278 5.602278
#> 1460 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1461 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1462 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1463 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1464 0.007345618 3.082202 81 81 5.602278 11.204556
#> 1465 0.007746254 3.044723 84 84 5.597433 15.265727
#> 1466 0.007746254 3.044723 84 84 5.597433 11.194866
#> 1467 0.007746254 3.044723 84 84 5.597433 11.194866
#> 1468 0.007746254 3.044723 84 84 5.597433 11.194866
#> 1469 0.007746254 3.044723 84 84 5.597433 10.833742
#> 1470 0.007746254 3.044723 84 84 5.597433 11.194866
#> 1471 0.007746254 3.044723 84 84 5.597433 11.580896
#> 1472 0.007444717 3.070310 82 82 5.595636 11.191271
#> 1473 0.007444717 3.070310 82 82 5.595636 10.830263
#> 1474 0.007444717 3.070310 82 82 5.595636 11.191271
#> 1475 0.007243730 3.076256 82 82 5.589111 11.178223
#> 1476 0.006830676 3.097913 81 81 5.581924 5.581924
#> 1477 0.006830676 3.097913 81 81 5.581924 5.676533
#> 1478 0.008339286 3.052078 81 81 5.571532 5.571532
#> 1479 0.008339286 3.052078 81 81 5.571532 11.143065
#> 1480 0.008339286 3.052078 81 81 5.571532 5.571532
#> 1481 0.008339286 3.052078 81 81 5.571532 11.143065
#> 1482 0.008339286 3.052078 81 81 5.571532 11.143065
#> 1483 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1484 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1485 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1486 0.007017543 3.107987 79 79 5.546070 22.184279
#> 1487 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1488 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1489 0.007017543 3.107987 79 79 5.546070 11.092140
#> 1490 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1491 0.007017543 3.107987 79 79 5.546070 11.092140
#> 1492 0.007017543 3.107987 79 79 5.546070 5.546070
#> 1493 0.007917341 3.037179 84 84 5.532980 10.708994
#> 1494 0.007917341 3.037179 84 84 5.532980 11.065960
#> 1495 0.007917341 3.037179 84 84 5.532980 16.598940
#> 1496 0.007917341 3.037179 84 84 5.532980 11.065960
#> 1497 0.007917341 3.037179 84 84 5.532980 11.065960
#> 1498 0.009413393 2.981889 86 86 5.523381 11.046762
#> 1499 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1500 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1501 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1502 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1503 0.009197813 2.994628 85 85 5.515390 22.061558
#> 1504 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1505 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1506 0.009197813 2.994628 85 85 5.515390 11.030779
#> 1507 0.006436894 3.144784 77 77 5.511655 5.511655
#> 1508 0.006436894 3.144784 77 77 5.511655 5.511655
#> 1509 0.006436894 3.144784 77 77 5.511655 5.511655
#> 1510 0.006436894 3.144784 77 77 5.511655 11.023309
#> 1511 0.006436894 3.144784 77 77 5.511655 22.046619
#> 1512 0.006436894 3.144784 77 77 5.511655 5.511655
#> 1513 0.006436894 3.144784 77 77 5.511655 5.511655
#> 1514 0.006436894 3.144784 77 77 5.511655 11.023309
#> 1515 0.006436894 3.144784 77 77 5.511655 11.023309
#> 1516 0.006436894 3.144784 77 77 5.511655 11.023309
#> 1517 0.007554303 3.071838 81 81 5.504927 11.009854
#> 1518 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1519 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1520 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1521 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1522 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1523 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1524 0.007920229 3.035684 84 84 5.498472 21.993889
#> 1525 0.007920229 3.035684 84 84 5.498472 219.938894
#> 1526 0.007920229 3.035684 84 84 5.498472 10.642205
#> 1527 0.007920229 3.035684 84 84 5.498472 10.642205
#> 1528 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1529 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1530 0.007920229 3.035684 84 84 5.498472 10.642205
#> 1531 0.007920229 3.035684 84 84 5.498472 10.996945
#> 1532 0.009208543 3.001584 84 84 5.496373 10.992747
#> 1533 0.009208543 3.001584 84 84 5.496373 10.992747
#> 1534 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1535 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1536 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1537 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1538 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1539 0.008945098 3.008082 84 84 5.495096 10.990192
#> 1540 0.008367352 3.055881 80 80 5.472739 5.472739
#> 1541 0.008367352 3.055881 80 80 5.472739 5.472739
#> 1542 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1543 0.008367352 3.055881 80 80 5.472739 5.472739
#> 1544 0.008367352 3.055881 80 80 5.472739 5.472739
#> 1545 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1546 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1547 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1548 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1549 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1550 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1551 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1552 0.008367352 3.055881 80 80 5.472739 10.945477
#> 1553 0.007303857 3.095567 79 79 5.467451 5.560120
#> 1554 0.007303857 3.095567 79 79 5.467451 49.207058
#> 1555 0.007303857 3.095567 79 79 5.467451 5.467451
#> 1556 0.007303857 3.095567 79 79 5.467451 5.467451
#> 1557 0.007303857 3.095567 79 79 5.467451 5.467451
#> 1558 0.007303857 3.095567 79 79 5.467451 10.934902
#> 1559 0.007303857 3.095567 79 79 5.467451 10.934902
#> 1560 0.007303857 3.095567 79 79 5.467451 10.934902
#> 1561 0.008753122 3.011747 84 84 5.465201 10.930402
#> 1562 0.008753122 3.011747 84 84 5.465201 10.930402
#> 1563 0.008753122 3.011747 84 84 5.465201 54.652008
#> 1564 0.008046923 3.063870 80 80 5.450676 5.450676
#> 1565 0.008046923 3.063870 80 80 5.450676 5.450676
#> 1566 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1567 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1568 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1569 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1570 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1571 0.008046923 3.063870 80 80 5.450676 10.901353
#> 1572 0.008046923 3.063870 80 80 5.450676 5.450676
#> 1573 0.007719673 3.039423 84 84 5.448766 10.897532
#> 1574 0.007719673 3.039423 84 84 5.448766 32.692597
#> 1575 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1576 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1577 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1578 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1579 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1580 0.007693063 3.064660 81 81 5.431977 10.863954
#> 1581 0.007991791 3.046753 82 82 5.414541 21.658166
#> 1582 0.007991791 3.046753 82 82 5.414541 10.829083
#> 1583 0.007991791 3.046753 82 82 5.414541 10.829083
#> 1584 0.007991791 3.046753 82 82 5.414541 10.829083
#> 1585 0.007991791 3.046753 82 82 5.414541 10.829083
#> 1586 0.007991791 3.046753 82 82 5.414541 10.829083
#> 1587 0.008377248 3.027632 83 83 5.412064 10.824127
#> 1588 0.008377248 3.027632 83 83 5.412064 10.824127
#> 1589 0.008377248 3.027632 83 83 5.412064 21.648255
#> 1590 0.006985661 3.112176 78 78 5.404289 10.808578
#> 1591 0.006985661 3.112176 78 78 5.404289 10.808578
#> 1592 0.006985661 3.112176 78 78 5.404289 5.404289
#> 1593 0.006985661 3.112176 78 78 5.404289 5.404289
#> 1594 0.006985661 3.112176 78 78 5.404289 5.404289
#> 1595 0.006985661 3.112176 78 78 5.404289 21.617156
#> 1596 0.007746254 3.044723 83 83 5.397004 21.588015
#> 1597 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1598 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1599 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1600 0.007746254 3.044723 83 83 5.397004 43.176030
#> 1601 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1602 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1603 0.007746254 3.044723 83 83 5.397004 21.588015
#> 1604 0.007746254 3.044723 83 83 5.397004 10.445814
#> 1605 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1606 0.007746254 3.044723 83 83 5.397004 10.794008
#> 1607 0.007345618 3.082202 80 80 5.391828 6.343328
#> 1608 0.007345618 3.082202 80 80 5.391828 5.391828
#> 1609 0.007345618 3.082202 80 80 5.391828 5.391828
#> 1610 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1611 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1612 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1613 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1614 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1615 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1616 0.007345618 3.082202 80 80 5.391828 10.783657
#> 1617 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1618 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1619 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1620 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1621 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1622 0.007444717 3.070310 81 81 5.388753 10.777506
#> 1623 0.007243730 3.076256 81 81 5.382077 21.528308
#> 1624 0.007243730 3.076256 81 81 5.382077 10.764154
#> 1625 0.007243730 3.076256 81 81 5.382077 10.764154
#> 1626 0.006830676 3.097913 80 80 5.371191 10.742382
#> 1627 0.006830676 3.097913 80 80 5.371191 10.742382
#> 1628 0.008339286 3.052078 80 80 5.364245 5.364245
#> 1629 0.008339286 3.052078 80 80 5.364245 10.728490
#> 1630 0.008339286 3.052078 80 80 5.364245 10.728490
#> 1631 0.008339286 3.052078 80 80 5.364245 10.728490
#> 1632 0.008339286 3.052078 80 80 5.364245 21.456980
#> 1633 0.008339286 3.052078 80 80 5.364245 10.728490
#> 1634 0.007917341 3.037179 83 83 5.335341 10.670681
#> 1635 0.007917341 3.037179 83 83 5.335341 25.609635
#> 1636 0.007917341 3.037179 83 83 5.335341 21.341362
#> 1637 0.007917341 3.037179 83 83 5.335341 26.676703
#> 1638 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1639 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1640 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1641 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1642 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1643 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1644 0.007017543 3.107987 78 78 5.330776 10.661552
#> 1645 0.007017543 3.107987 78 78 5.330776 10.661552
#> 1646 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1647 0.007017543 3.107987 78 78 5.330776 5.330776
#> 1648 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1649 0.009197813 2.994628 84 84 5.323348 10.303255
#> 1650 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1651 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1652 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1653 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1654 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1655 0.009197813 2.994628 84 84 5.323348 21.293394
#> 1656 0.009197813 2.994628 84 84 5.323348 10.646697
#> 1657 0.009208543 3.001584 83 83 5.302301 10.604603
#> 1658 0.009208543 3.001584 83 83 5.302301 10.604603
#> 1659 0.009208543 3.001584 83 83 5.302301 10.604603
#> 1660 0.009208543 3.001584 83 83 5.302301 10.970279
#> 1661 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1662 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1663 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1664 0.007920229 3.035684 83 83 5.302160 21.208642
#> 1665 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1666 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1667 0.007920229 3.035684 83 83 5.302160 84.834567
#> 1668 0.007920229 3.035684 83 83 5.302160 30.786738
#> 1669 0.007920229 3.035684 83 83 5.302160 10.604321
#> 1670 0.008945098 3.008082 83 83 5.300657 21.202627
#> 1671 0.008945098 3.008082 83 83 5.300657 10.601314
#> 1672 0.008945098 3.008082 83 83 5.300657 10.601314
#> 1673 0.008945098 3.008082 83 83 5.300657 10.601314
#> 1674 0.008945098 3.008082 83 83 5.300657 63.607881
#> 1675 0.008945098 3.008082 83 83 5.300657 31.803941
#> 1676 0.008945098 3.008082 83 83 5.300657 10.601314
#> 1677 0.008945098 3.008082 83 83 5.300657 10.601314
#> 1678 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1679 0.007554303 3.071838 80 80 5.298817 10.963069
#> 1680 0.007554303 3.071838 80 80 5.298817 5.298817
#> 1681 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1682 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1683 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1684 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1685 0.007554303 3.071838 80 80 5.298817 10.597634
#> 1686 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1687 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1688 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1689 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1690 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1691 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1692 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1693 0.006436894 3.144784 76 76 5.289671 10.579342
#> 1694 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1695 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1696 0.006436894 3.144784 76 76 5.289671 5.289671
#> 1697 0.008753122 3.011747 83 83 5.271588 10.543175
#> 1698 0.008753122 3.011747 83 83 5.271588 10.543175
#> 1699 0.008753122 3.011747 83 83 5.271588 10.543175
#> 1700 0.008367352 3.055881 79 79 5.266362 10.532725
#> 1701 0.008367352 3.055881 79 79 5.266362 5.355623
#> 1702 0.008367352 3.055881 79 79 5.266362 21.065449
#> 1703 0.008367352 3.055881 79 79 5.266362 5.266362
#> 1704 0.008367352 3.055881 79 79 5.266362 5.266362
#> 1705 0.008367352 3.055881 79 79 5.266362 5.266362
#> 1706 0.008367352 3.055881 79 79 5.266362 5.266362
#> 1707 0.008367352 3.055881 79 79 5.266362 5.266362
#> 1708 0.008367352 3.055881 79 79 5.266362 10.532725
#> 1709 0.008367352 3.055881 79 79 5.266362 21.065449
#> 1710 0.007303857 3.095567 78 78 5.256040 5.256040
#> 1711 0.007303857 3.095567 78 78 5.256040 47.304364
#> 1712 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1713 0.007303857 3.095567 78 78 5.256040 5.256040
#> 1714 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1715 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1716 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1717 0.007303857 3.095567 78 78 5.256040 31.536243
#> 1718 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1719 0.007303857 3.095567 78 78 5.256040 21.024162
#> 1720 0.007303857 3.095567 78 78 5.256040 10.512081
#> 1721 0.007303857 3.095567 78 78 5.256040 21.024162
#> 1722 0.008046923 3.063870 79 79 5.244605 5.244605
#> 1723 0.008046923 3.063870 79 79 5.244605 5.158628
#> 1724 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1725 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1726 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1727 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1728 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1729 0.008046923 3.063870 79 79 5.244605 20.978421
#> 1730 0.008046923 3.063870 79 79 5.244605 10.489210
#> 1731 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1732 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1733 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1734 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1735 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1736 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1737 0.007693063 3.064660 80 80 5.229064 8.941700
#> 1738 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1739 0.007693063 3.064660 80 80 5.229064 10.458129
#> 1740 0.008377248 3.027632 82 82 5.217047 10.434093
#> 1741 0.008377248 3.027632 82 82 5.217047 10.434093
#> 1742 0.008377248 3.027632 82 82 5.217047 10.434093
#> 1743 0.008377248 3.027632 82 82 5.217047 10.434093
#> 1744 0.008377248 3.027632 82 82 5.217047 10.434093
#> 1745 0.007991791 3.046753 81 81 5.215861 10.431723
#> 1746 0.007991791 3.046753 81 81 5.215861 20.863446
#> 1747 0.007991791 3.046753 81 81 5.215861 10.431723
#> 1748 0.007991791 3.046753 81 81 5.215861 10.431723
#> 1749 0.007991791 3.046753 81 81 5.215861 10.431723
#> 1750 0.007991791 3.046753 81 81 5.215861 10.431723
#> 1751 0.007746254 3.044723 82 82 5.201452 10.067326
#> 1752 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1753 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1754 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1755 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1756 0.007746254 3.044723 82 82 5.201452 15.604355
#> 1757 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1758 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1759 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1760 0.007746254 3.044723 82 82 5.201452 10.067326
#> 1761 0.007746254 3.044723 82 82 5.201452 20.805807
#> 1762 0.007746254 3.044723 82 82 5.201452 10.402903
#> 1763 0.006985661 3.112176 77 77 5.191565 10.383130
#> 1764 0.006985661 3.112176 77 77 5.191565 5.191565
#> 1765 0.006985661 3.112176 77 77 5.191565 5.191565
#> 1766 0.006985661 3.112176 77 77 5.191565 5.191565
#> 1767 0.006985661 3.112176 77 77 5.191565 5.191565
#> 1768 0.006985661 3.112176 77 77 5.191565 31.149391
#> 1769 0.007444717 3.070310 80 80 5.187091 10.374181
#> 1770 0.007345618 3.082202 79 79 5.186786 5.186786
#> 1771 0.007345618 3.082202 79 79 5.186786 5.186786
#> 1772 0.007345618 3.082202 79 79 5.186786 10.373572
#> 1773 0.007345618 3.082202 79 79 5.186786 20.747144
#> 1774 0.007345618 3.082202 79 79 5.186786 20.747144
#> 1775 0.007345618 3.082202 79 79 5.186786 10.373572
#> 1776 0.007345618 3.082202 79 79 5.186786 10.373572
#> 1777 0.007345618 3.082202 79 79 5.186786 10.373572
#> 1778 0.007345618 3.082202 79 79 5.186786 20.747144
#> 1779 0.007243730 3.076256 80 80 5.180282 10.360564
#> 1780 0.007243730 3.076256 80 80 5.180282 10.360564
#> 1781 0.007243730 3.076256 80 80 5.180282 25.901411
#> 1782 0.007243730 3.076256 80 80 5.180282 10.360564
#> 1783 0.007243730 3.076256 80 80 5.180282 10.360564
#> 1784 0.007243730 3.076256 80 80 5.180282 15.540847
#> 1785 0.007243730 3.076256 80 80 5.180282 10.360564
#> 1786 0.006830676 3.097913 79 79 5.165912 5.165912
#> 1787 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1788 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1789 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1790 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1791 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1792 0.006830676 3.097913 79 79 5.165912 10.331824
#> 1793 0.008339286 3.052078 79 79 5.162207 5.162207
#> 1794 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1795 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1796 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1797 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1798 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1799 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1800 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1801 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1802 0.008339286 3.052078 79 79 5.162207 10.324414
#> 1803 0.007917341 3.037179 82 82 5.142493 10.639641
#> 1804 0.007917341 3.037179 82 82 5.142493 10.284986
#> 1805 0.007917341 3.037179 82 82 5.142493 10.284986
#> 1806 0.007917341 3.037179 82 82 5.142493 56.567424
#> 1807 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1808 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1809 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1810 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1811 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1812 0.009197813 2.994628 83 83 5.135814 20.543254
#> 1813 0.009197813 2.994628 83 83 5.135814 10.271627
#> 1814 0.009197813 2.994628 83 83 5.135814 32.252909
#> 1815 0.009197813 2.994628 83 83 5.135814 20.543254
#> 1816 0.009197813 2.994628 83 83 5.135814 20.543254
#> 1817 0.009197813 2.994628 83 83 5.135814 25.679068
#> 1818 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1819 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1820 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1821 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1822 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1823 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1824 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1825 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1826 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1827 0.007017543 3.107987 77 77 5.121223 15.363668
#> 1828 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1829 0.007017543 3.107987 77 77 5.121223 5.121223
#> 1830 0.009208543 3.001584 82 82 5.112853 10.225707
#> 1831 0.009208543 3.001584 82 82 5.112853 10.225707
#> 1832 0.009208543 3.001584 82 82 5.112853 10.225707
#> 1833 0.009208543 3.001584 82 82 5.112853 20.451414
#> 1834 0.009208543 3.001584 82 82 5.112853 10.225707
#> 1835 0.009208543 3.001584 82 82 5.112853 10.225707
#> 1836 0.008945098 3.008082 82 82 5.110865 9.891997
#> 1837 0.008945098 3.008082 82 82 5.110865 10.574204
#> 1838 0.008945098 3.008082 82 82 5.110865 10.221730
#> 1839 0.008945098 3.008082 82 82 5.110865 10.221730
#> 1840 0.008945098 3.008082 82 82 5.110865 10.221730
#> 1841 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1842 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1843 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1844 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1845 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1846 0.007920229 3.035684 82 82 5.110605 81.769676
#> 1847 0.007920229 3.035684 82 82 5.110605 9.891493
#> 1848 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1849 0.007920229 3.035684 82 82 5.110605 10.221209
#> 1850 0.007554303 3.071838 79 79 5.097976 10.195952
#> 1851 0.007554303 3.071838 79 79 5.097976 10.195952
#> 1852 0.007554303 3.071838 79 79 5.097976 10.195952
#> 1853 0.008753122 3.011747 82 82 5.082611 10.165222
#> 1854 0.008753122 3.011747 82 82 5.082611 10.165222
#> 1855 0.008753122 3.011747 82 82 5.082611 10.165222
#> 1856 0.008753122 3.011747 82 82 5.082611 10.165222
#> 1857 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1858 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1859 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1860 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1861 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1862 0.006436894 3.144784 75 75 5.073864 15.221592
#> 1863 0.006436894 3.144784 75 75 5.073864 15.221592
#> 1864 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1865 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1866 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1867 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1868 0.006436894 3.144784 75 75 5.073864 15.221592
#> 1869 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1870 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1871 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1872 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1873 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1874 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1875 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1876 0.006436894 3.144784 75 75 5.073864 20.295456
#> 1877 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1878 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1879 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1880 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1881 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1882 0.006436894 3.144784 75 75 5.073864 5.073864
#> 1883 0.006436894 3.144784 75 75 5.073864 10.147728
#> 1884 0.008367352 3.055881 78 78 5.065288 5.065288
#> 1885 0.008367352 3.055881 78 78 5.065288 5.065288
#> 1886 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1887 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1888 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1889 0.008367352 3.055881 78 78 5.065288 15.195863
#> 1890 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1891 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1892 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1893 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1894 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1895 0.008367352 3.055881 78 78 5.065288 10.130575
#> 1896 0.007719673 3.039423 82 82 5.063949 10.477135
#> 1897 0.007719673 3.039423 82 82 5.063949 10.127897
#> 1898 0.007303857 3.095567 77 77 5.050234 5.050234
#> 1899 0.007303857 3.095567 77 77 5.050234 45.452108
#> 1900 0.007303857 3.095567 77 77 5.050234 5.050234
#> 1901 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1902 0.007303857 3.095567 77 77 5.050234 5.050234
#> 1903 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1904 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1905 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1906 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1907 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1908 0.007303857 3.095567 77 77 5.050234 20.200937
#> 1909 0.007303857 3.095567 77 77 5.050234 10.100468
#> 1910 0.008046923 3.063870 78 78 5.043848 5.043848
#> 1911 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1912 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1913 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1914 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1915 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1916 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1917 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1918 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1919 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1920 0.008046923 3.063870 78 78 5.043848 5.043848
#> 1921 0.008046923 3.063870 78 78 5.043848 10.087696
#> 1922 0.008046923 3.063870 78 78 5.043848 8.877172
#> 1923 0.008046923 3.063870 78 78 5.043848 10.087696
#> [ reached 'max' / getOption("max.print") -- omitted 273542 rows ]
hlcodL <- hlcodL %>% filter(weight_kg < 100)
ggplot(hlcodL, aes(weight_kg, length_cm2)) +
geom_point() +
facet_wrap(~Year)
# Now do the same for flounder
# First standardize length to cm and then check how zero-catches are implemented at this stage
hlfleL <- hlfleL %>%
mutate(length_cm = ifelse(LngtCode %in% c(".", "0"),
LngtClass/10,
LngtClass)) # Standardize length (https://vocab.ices.dk/?ref=18)
filter(hlfleL, length_cm == 0) # No such thing
#> # A tibble: 0 × 49
#> # … with 49 variables: RecordType <chr>, Survey <chr>, Quarter <int>,
#> # Country <chr>, Ship <chr>, Gear <chr>, SweepLngt <int>, GearEx <chr>,
#> # DoorType <lgl>, StNo <chr>, HaulNo <int>, Year <int>, SpecCodeType <chr>,
#> # SpecCode <int>, SpecVal <fct>, Sex <chr>, TotalNo <dbl>,
#> # CatIdentifier <int>, NoMeas <int>, SubFactor <dbl>, SubWgt <int>,
#> # CatCatchWgt <int>, LngtCode <chr>, LngtClass <int>, HLNoAtLngt <dbl>,
#> # DevStage <chr>, LenMeasType <int>, DateofCalculation <int>, …
bits_ca_fle <- bits_ca_fle %>%
drop_na(IndWgt) %>%
drop_na(LngtClass) %>%
filter(IndWgt > 0 & LngtClass > 0) %>% # Filter positive length and weight
mutate(weight_kg = IndWgt/1000) %>%
mutate(length_cm = ifelse(LngtCode == ".",
LngtClass/10,
LngtClass)) %>% # Standardize length ((https://vocab.ices.dk/?ref=18))
mutate(keep = ifelse(LngtCode == "." & Year == 2008, "N", "Y")) %>%
filter(keep == "Y") %>%
filter(length_cm < 70)
# Now check if all rows where length is NA are the ones with zero catch!
hlfleL %>%
mutate(length2 = replace_na(length_cm, -9),
no_length = ifelse(length2 < 0, "T", "F")) %>%
ggplot(., aes(length2, CPUEun, color = no_length)) + geom_point(alpha = 0.2) + facet_wrap(~no_length)
#> Warning: Removed 42 rows containing missing values (geom_point).
hlfleL %>% mutate(length2 = replace_na(length_cm, -9)) %>% group_by(length2) %>% distinct(CPUEun) %>% arrange(CPUEun)
#> # A tibble: 12,467 × 2
#> # Groups: length2 [253]
#> CPUEun length2
#> <dbl> <dbl>
#> 1 0 -9
#> 2 0.667 19
#> 3 0.667 21
#> 4 0.667 35
#> 5 0.667 39
#> 6 0.667 40
#> 7 0.667 42
#> 8 0.870 27
#> 9 0.870 32
#> 10 0.870 37.5
#> # … with 12,457 more rows
# Right, so all hauls with zero catch have NA length_cm. I don't have any NA catches
t <- hlfleL %>% drop_na(CPUEun)
# Well, 11 rows. I will remove them
hlfleL <- hlfleL %>% drop_na(CPUEun)
t <- hlfleL %>% filter(CPUEun == 0)
t <- hlfleL %>% drop_na(length_cm)
# In other words, a zero catch is when the catch is zero and length_cm is NA
# In order to not get any NA CPUEs in unit biomass because length is NA (I want them instead
# to be 0, as the numbers-CPUE is), I will replace length_cm == NA with length_cm == 0 before
# calculating biomass cpue
hlfleL <- hlfleL %>% mutate(length_cm2 = replace_na(length_cm, 0))
# Standardize length in the haul-data and calculate weight
hlfleL <- hlfleL %>%
mutate(weight_kg = (a*length_cm2^b)/1000) %>%
mutate(CPUEun_kg = weight_kg*CPUEun)
# Plot and check it's correct also in this data
ggplot(hlfleL, aes(weight_kg, length_cm2)) +
geom_point() +
facet_wrap(~Year)
#> Warning: Removed 3311 rows containing missing values (geom_point).
# Check
t <- hlfleL %>% drop_na(CPUEun_kg) # Should not have any NA in biomass-catch
t <- hlfleL %>% filter(CPUEun_kg == 0) # Should result in a few percent of rows (note this is not proportion of hauls, but rows)
t <- hlfleL %>% drop_na(length_cm2) # Should be no NA
# What is the proportion of zero-catch hauls?
cod_0plot <- hlcodL %>%
group_by(haul.id, Year, Quarter) %>%
summarise(CPUEun_haul = sum(CPUEun)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
group_by(Year, Quarter, zero_catch) %>%
summarise(n = n()) %>%
ungroup() %>%
pivot_wider(names_from = zero_catch, values_from = n) %>%
mutate(prop_zero_catch_hauls = Y/(N+Y)) %>%
ggplot(., aes(Year, prop_zero_catch_hauls)) + geom_bar(stat = "identity") +
coord_cartesian(expand = 0, ylim = c(0, 1)) +
facet_wrap(~ Quarter) +
ggtitle("Cod")
# How many zero-catch hauls?
fle_0plot <- hlfleL %>%
group_by(haul.id, Year, Quarter) %>%
summarise(CPUEun_haul = sum(CPUEun)) %>%
ungroup() %>%
mutate(zero_catch = ifelse(CPUEun_haul == 0, "Y", "N")) %>%
group_by(Year, Quarter, zero_catch) %>%
summarise(n = n()) %>%
ungroup() %>%
pivot_wider(names_from = zero_catch, values_from = n) %>%
mutate(prop_zero_catch_hauls = Y/(N+Y)) %>%
ggplot(., aes(Year, prop_zero_catch_hauls)) + geom_bar(stat = "identity") +
coord_cartesian(expand = 0, ylim = c(0, 1)) +
facet_wrap(~ Quarter) +
ggtitle("Flounder")
cod_0plot / fle_0plot
#> Warning: Removed 1 rows containing missing values (position_stack).
#> Warning: Removed 1 rows containing missing values (position_stack).
Standardize according to Orio
To get unit: kg of fish caught by trawling for 1 h a standard bottom swept area of 0.45km2 using a TVL trawl with 75 m sweeps at the standard speed of three knots
# Remove hauls done with the TVL gear with a SweepLngt < 50 (these are calibration hauls, pers. com. Anders & Ale)
# And also hauls without length-information
# Remove pelagic gear
hlcodL <- hlcodL %>%
mutate(SweepLngt2 = replace_na(SweepLngt, 50)) %>%
mutate(keep = ifelse(Gear == "TVL" & SweepLngt2 < 50, "N", "Y")) %>%
filter(keep == "Y") %>%
dplyr::select(-keep, -SweepLngt2) %>%
filter(!Gear == "PEL")
hlfleL <- hlfleL %>%
mutate(SweepLngt2 = replace_na(SweepLngt, 50)) %>%
mutate(keep = ifelse(Gear == "TVL" & SweepLngt2 < 50, "N", "Y")) %>%
filter(keep == "Y") %>%
dplyr::select(-keep, -SweepLngt2) %>%
filter(!Gear == "PEL")
# Add in RS and RSA-values from the sweep file
# CPUE should be multiplied with RS and RSA to standardize to a relative speed and gear dimension.
# There is not a single file will all RS and RSA values. Instead they come in three files:
# - sweep (non-Swedish hauls between 1991-2016)
# - + calculated based on trawl speed and gear dimensions.
# I will join in the RS and RSA values from all sources, then standardize and filter
# away non-standardized hauls
# sort(unique(sweep$Year))
# sort(unique(sweep$Country))
# Since I don't have the sweep data for Swedish data, I have to calculate it from scratch using the
# equation in Orio's spreadsheet
# First I will join in the sweep data,
sweep_sel <- sweep %>% rename("haul.id" = "ï..haul.id") %>% dplyr::select(haul.id, RSA, RS)
hlcodL2 <- left_join(hlcodL, sweep_sel)
hlfleL2 <- left_join(hlfleL, sweep_sel)
hlcodL2 <- hlcodL2 %>%
rename("RS_sweep" = "RS",
"RSA_sweep" = "RSA") %>%
mutate(RS_sweep = as.numeric(RS_sweep),
RSA_sweep = as.numeric(RSA_sweep))
hlfleL2 <- hlfleL2 %>%
rename("RS_sweep" = "RS",
"RSA_sweep" = "RSA") %>%
mutate(RS_sweep = as.numeric(RS_sweep),
RSA_sweep = as.numeric(RSA_sweep))
sort(colnames(hlcodL2))
#> [1] "a" "b" "BySpecRecCode"
#> [4] "CatCatchWgt" "CatIdentifier" "Country"
#> [7] "CPUEun" "CPUEun_kg" "DataType"
#> [10] "DateofCalculation" "DevStage" "DoorType"
#> [13] "Fishing.line" "Gear" "GearEx"
#> [16] "GroundSpeed" "haul.id" "HaulDur"
#> [19] "HaulNo" "HaulVal" "HLNoAtLngt"
#> [22] "IDx" "length_cm" "length_cm2"
#> [25] "LenMeasType" "LngtClass" "LngtCode"
#> [28] "NoMeas" "Quarter" "RecordType"
#> [31] "Rect" "RS_sweep" "RSA_sweep"
#> [34] "Sex" "Ship" "Ship2"
#> [37] "Ship3" "ShootLat" "ShootLong"
#> [40] "SpecCode" "SpecCodeType" "Species"
#> [43] "SpecVal" "StdSpecRecCode" "StNo"
#> [46] "sub_div" "SubFactor" "SubWgt"
#> [49] "Survey" "SweepLngt" "TotalNo"
#> [52] "Valid_Aphia" "weight_kg" "Year"
sort(colnames(hlfleL2))
#> [1] "a" "b" "BySpecRecCode"
#> [4] "CatCatchWgt" "CatIdentifier" "Country"
#> [7] "CPUEun" "CPUEun_kg" "DataType"
#> [10] "DateofCalculation" "DevStage" "DoorType"
#> [13] "Fishing.line" "Gear" "GearEx"
#> [16] "GroundSpeed" "haul.id" "HaulDur"
#> [19] "HaulNo" "HaulVal" "HLNoAtLngt"
#> [22] "IDx" "length_cm" "length_cm2"
#> [25] "LenMeasType" "LngtClass" "LngtCode"
#> [28] "NoMeas" "Quarter" "RecordType"
#> [31] "Rect" "RS_sweep" "RSA_sweep"
#> [34] "Sex" "Ship" "Ship2"
#> [37] "Ship3" "ShootLat" "ShootLong"
#> [40] "SpecCode" "SpecCodeType" "Species"
#> [43] "SpecVal" "StdSpecRecCode" "StNo"
#> [46] "sub_div" "SubFactor" "SubWgt"
#> [49] "Survey" "SweepLngt" "TotalNo"
#> [52] "Valid_Aphia" "weight_kg" "Year"
# I will calculate a RS and RSA column in the catch data based on Ale's equation in the sweep file:
sort(unique(hlcodL2$GroundSpeed))
#> [1] -9.0 0.1 0.2 0.8 1.7 1.8 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8
#> [16] 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.0 4.1 4.2 4.3
#> [31] 4.4 4.5 4.6 4.7 4.9 5.0 5.2 5.3 5.4 5.5 5.6 5.7 5.9 6.0 6.1
#> [46] 6.2 6.3 6.6 6.7 6.8 6.9 7.1 7.3 8.6
sort(unique(hlcodL2$Fishing.line))
#> [1] -9.00 16.54 28.00 33.22 35.20 36.00 39.80 63.46 83.00 160.00
sort(unique(hlcodL2$SweepLngt))
#> [1] 0 40 50 60 75 87 90 95 100 110 125 135 180 182 185 188 200 203 225
#> [20] 235
# First replace -9 in the columns I use for the calculations with NA so I don't end up with real numbers that are wrong!
hlcodL2 <- hlcodL2 %>% mutate(GroundSpeed = ifelse(GroundSpeed == -9, NA, GroundSpeed),
Fishing.line = ifelse(Fishing.line == -9, NA, Fishing.line),
SweepLngt = ifelse(SweepLngt == -9, NA, SweepLngt))
hlfleL2 <- hlfleL2 %>% mutate(GroundSpeed = ifelse(GroundSpeed == -9, NA, GroundSpeed),
Fishing.line = ifelse(Fishing.line == -9, NA, Fishing.line),
SweepLngt = ifelse(SweepLngt == -9, NA, SweepLngt))
hlcodL2 %>% filter(Quarter == 1) %>%
distinct(GroundSpeed, Fishing.line, SweepLngt) %>% as.data.frame()
#> SweepLngt Fishing.line GroundSpeed
#> 1 NA NA NA
#> 2 NA 35.20 3.5
#> 3 NA 28.00 NA
#> 4 NA 35.20 3.6
#> 5 NA 35.20 3.4
#> 6 NA 36.00 NA
#> 7 110 NA NA
#> 8 NA 39.80 NA
#> 9 60 NA NA
#> 10 NA 35.20 NA
#> 11 NA 35.20 3.0
#> 12 NA 35.20 3.1
#> 13 NA 35.20 3.2
#> 14 NA 36.00 3.0
#> 15 50 160.00 3.3
#> 16 50 160.00 3.2
#> 17 50 160.00 3.0
#> 18 50 160.00 3.1
#> 19 50 160.00 3.4
#> 20 100 160.00 3.1
#> 21 50 160.00 2.8
#> 22 50 160.00 2.7
#> 23 185 83.00 3.1
#> 24 125 83.00 3.1
#> 25 185 83.00 3.2
#> 26 185 83.00 3.3
#> 27 50 160.00 2.9
#> 28 NA 36.00 3.8
#> 29 NA 36.00 3.6
#> 30 NA 36.00 4.0
#> 31 NA 36.00 4.6
#> 32 NA 36.00 3.4
#> 33 NA 36.00 4.2
#> 34 NA 36.00 3.2
#> 35 NA 36.00 2.6
#> 36 NA 36.00 2.8
#> 37 50 160.00 2.6
#> 38 185 83.00 3.0
#> 39 185 83.00 2.8
#> 40 185 83.00 3.4
#> 41 185 83.00 3.5
#> 42 185 83.00 2.7
#> 43 185 83.00 2.9
#> 44 NA 36.00 4.4
#> 45 NA 36.00 2.4
#> 46 180 83.00 3.1
#> 47 180 83.00 3.2
#> 48 180 83.00 3.0
#> 49 180 83.00 3.3
#> 50 180 83.00 3.4
#> 51 180 83.00 3.5
#> 52 180 83.00 2.8
#> 53 180 83.00 3.9
#> 54 NA 36.00 3.7
#> 55 NA 36.00 3.1
#> 56 NA NA 3.2
#> 57 NA NA 3.3
#> 58 NA NA 3.6
#> 59 NA NA 3.4
#> 60 90 160.00 3.4
#> 61 NA NA 3.0
#> 62 NA NA 3.8
#> 63 NA NA 3.9
#> 64 NA NA 3.7
#> 65 90 160.00 3.2
#> 66 90 160.00 3.8
#> 67 90 160.00 3.7
#> 68 90 160.00 3.5
#> 69 90 160.00 3.6
#> 70 90 160.00 3.0
#> 71 90 160.00 3.9
#> 72 NA NA 4.3
#> 73 NA NA 3.1
#> 74 NA NA 4.9
#> 75 NA NA 4.0
#> 76 NA NA 4.6
#> 77 NA NA 2.9
#> 78 NA NA 4.2
#> 79 NA NA 3.5
#> 80 NA NA 4.7
#> 81 203 83.00 3.8
#> 82 203 83.00 3.5
#> 83 203 83.00 3.9
#> 84 203 83.00 3.7
#> 85 203 83.00 4.0
#> 86 NA NA 2.8
#> 87 203 83.00 3.6
#> 88 203 83.00 3.4
#> 89 NA NA 2.6
#> 90 NA NA 2.7
#> 91 NA NA 2.4
#> 92 NA NA 4.1
#> 93 235 83.00 3.7
#> 94 235 83.00 4.1
#> 95 235 83.00 3.9
#> 96 235 83.00 3.8
#> 97 235 83.00 3.0
#> 98 235 83.00 3.6
#> 99 235 83.00 4.0
#> 100 235 83.00 3.1
#> 101 235 83.00 3.5
#> 102 135 83.00 3.9
#> 103 135 83.00 3.7
#> 104 135 83.00 3.5
#> 105 135 83.00 3.6
#> 106 135 83.00 3.2
#> 107 225 83.00 3.5
#> 108 225 83.00 3.4
#> 109 225 83.00 2.7
#> 110 225 83.00 3.3
#> 111 225 83.00 3.6
#> 112 225 83.00 3.2
#> 113 225 83.00 3.7
#> 114 0 83.00 3.6
#> 115 225 83.00 3.1
#> 116 NA 63.46 NA
#> 117 NA NA 4.4
#> 118 NA 36.00 1.7
#> 119 203 83.00 3.3
#> 120 NA 36.00 3.9
#> 121 75 63.46 3.1
#> 122 75 63.46 3.2
#> 123 75 63.46 3.0
#> 124 75 63.46 2.6
#> 125 75 63.46 2.9
#> 126 235 83.00 3.2
#> 127 235 83.00 3.3
#> 128 235 83.00 3.4
#> 129 100 160.00 3.6
#> 130 100 160.00 3.8
#> 131 100 160.00 3.5
#> 132 100 160.00 3.7
#> 133 100 160.00 3.4
#> 134 100 160.00 3.3
#> 135 NA 33.22 3.1
#> 136 NA 33.22 3.3
#> 137 NA 33.22 3.0
#> 138 NA 33.22 3.2
#> 139 NA 33.22 3.4
#> 140 NA 63.46 3.1
#> 141 NA 63.46 3.0
#> 142 NA 63.46 2.8
#> 143 NA 63.46 2.9
#> 144 75 63.46 2.7
#> 145 75 63.46 2.8
#> 146 NA 63.46 3.2
#> 147 75 33.22 NA
#> 148 NA 63.46 3.3
#> 149 NA 63.46 3.4
#> 150 75 63.46 3.3
#> 151 NA 33.22 2.9
#> 152 75 63.46 2.4
#> 153 NA 33.22 2.8
#> 154 60 63.46 3.0
#> 155 60 63.46 2.9
#> 156 60 63.46 3.1
#> 157 60 63.46 2.8
#> 158 NA 63.46 2.5
#> 159 NA 63.46 2.7
#> 160 95 63.46 3.1
#> 161 95 63.46 3.0
#> 162 NA 33.22 NA
#> 163 95 63.46 NA
#> 164 NA 33.22 3.5
#> 165 NA 33.22 3.6
#> 166 75 63.46 NA
#> 167 95 63.46 2.9
#> 168 NA 63.46 3.7
#> 169 NA 63.46 2.2
#> 170 NA 33.22 3.8
#> 171 NA 63.46 2.3
#> 172 NA 63.46 2.6
#> 173 NA 33.22 3.7
#> 174 NA 33.22 2.7
#> 175 NA 63.46 2.0
#> 176 NA 63.46 0.1
#> 177 NA 63.46 2.1
#> 178 NA 63.46 1.7
#> 179 NA 63.46 2.4
#> 180 NA 33.22 2.6
#> 181 NA 63.46 3.9
#> 182 NA 33.22 2.3
#> 183 200 33.22 2.9
#> 184 NA 63.46 8.6
#> 185 75 63.46 3.4
#> 186 NA 63.46 0.2
#> 187 75 63.46 3.6
#> 188 75 63.46 3.5
#> 189 75 63.46 2.5
#> 190 NA 16.54 3.4
#> 191 185 83.00 2.6
#> 192 50 160.00 3.6
#> 193 203 83.00 3.2
#> 194 110 160.00 3.6
#> 195 110 160.00 3.1
#> 196 110 160.00 3.4
#> 197 NA 63.46 3.6
#> 198 NA 63.46 3.8
#> 199 NA 63.46 4.2
#> 200 NA 63.46 5.5
#> 201 NA 63.46 5.2
#> 202 NA 63.46 6.6
#> 203 NA 63.46 5.0
#> 204 NA 63.46 6.1
#> 205 NA 63.46 6.2
#> 206 NA 63.46 6.0
#> 207 NA 63.46 5.9
#> 208 NA 63.46 6.8
#> 209 NA 63.46 4.1
#> 210 NA 63.46 4.3
hlcodL2 %>% filter(Quarter == 4) %>%
distinct(GroundSpeed, Fishing.line, SweepLngt) %>% as.data.frame()
#> SweepLngt Fishing.line GroundSpeed
#> 1 NA 36.00 NA
#> 2 NA 36.00 3.4
#> 3 NA 36.00 3.6
#> 4 NA 36.00 3.2
#> 5 NA 36.00 3.8
#> 6 NA 36.00 4.0
#> 7 180 83.00 2.9
#> 8 180 83.00 2.8
#> 9 180 83.00 3.1
#> 10 NA 36.00 4.2
#> 11 180 83.00 3.2
#> 12 180 83.00 3.3
#> 13 180 83.00 3.0
#> 14 NA 36.00 3.0
#> 15 185 83.00 2.8
#> 16 185 83.00 3.0
#> 17 185 83.00 3.2
#> 18 185 83.00 3.3
#> 19 185 83.00 3.1
#> 20 185 83.00 3.5
#> 21 185 83.00 3.4
#> 22 185 83.00 3.6
#> 23 203 83.00 3.6
#> 24 203 83.00 3.7
#> 25 203 83.00 3.5
#> 26 203 83.00 3.8
#> 27 203 83.00 3.9
#> 28 203 83.00 3.4
#> 29 100 160.00 3.4
#> 30 100 83.00 3.5
#> 31 100 83.00 3.4
#> 32 225 83.00 3.6
#> 33 225 83.00 3.5
#> 34 100 83.00 4.0
#> 35 100 160.00 3.5
#> 36 100 83.00 3.7
#> 37 100 83.00 3.3
#> 38 100 83.00 3.2
#> 39 100 83.00 3.6
#> 40 225 83.00 3.3
#> 41 225 83.00 3.4
#> 42 180 83.00 3.6
#> 43 NA 28.00 NA
#> 44 225 83.00 3.2
#> 45 180 83.00 3.4
#> 46 180 83.00 3.5
#> 47 225 83.00 3.7
#> 48 225 83.00 3.8
#> 49 185 83.00 3.8
#> 50 225 83.00 3.9
#> 51 185 83.00 3.7
#> 52 NA 36.00 1.7
#> 53 NA 63.46 NA
#> 54 40 160.00 3.7
#> 55 100 160.00 3.1
#> 56 100 160.00 3.3
#> 57 225 83.00 3.0
#> 58 40 160.00 3.4
#> 59 100 160.00 3.2
#> 60 100 160.00 3.7
#> 61 NA NA 3.2
#> 62 NA 63.46 2.9
#> 63 NA 63.46 3.0
#> 64 NA NA 4.1
#> 65 75 63.46 3.1
#> 66 75 63.46 3.4
#> 67 75 63.46 2.9
#> 68 NA 63.46 3.1
#> 69 NA 63.46 2.8
#> 70 75 63.46 NA
#> 71 75 63.46 2.8
#> 72 75 63.46 3.7
#> 73 NA 63.46 3.2
#> 74 NA NA NA
#> 75 75 63.46 2.7
#> 76 75 160.00 3.5
#> 77 75 160.00 3.4
#> 78 75 160.00 3.3
#> 79 75 160.00 3.7
#> 80 75 160.00 3.8
#> 81 75 160.00 3.2
#> 82 NA 33.22 3.0
#> 83 75 160.00 3.6
#> 84 NA 33.22 3.2
#> 85 NA 33.22 2.8
#> 86 NA 33.22 3.4
#> 87 NA 33.22 NA
#> 88 NA 63.46 2.7
#> 89 NA 33.22 3.6
#> 90 75 63.46 3.0
#> 91 NA 33.22 3.1
#> 92 NA 33.22 3.3
#> 93 NA 33.22 2.9
#> 94 75 63.46 3.2
#> 95 75 63.46 2.5
#> 96 NA 33.22 3.7
#> 97 NA 33.22 3.5
#> 98 75 63.46 3.3
#> 99 50 63.46 3.0
#> 100 NA 63.46 2.5
#> 101 75 33.22 NA
#> 102 NA 63.46 3.3
#> 103 50 63.46 2.9
#> 104 50 63.46 3.3
#> 105 95 63.46 2.9
#> 106 95 63.46 3.0
#> 107 95 63.46 2.6
#> 108 87 63.46 2.9
#> 109 87 63.46 3.0
#> 110 NA 63.46 3.6
#> 111 NA 63.46 3.5
#> 112 NA 63.46 3.4
#> 113 NA 33.22 1.8
#> 114 NA 63.46 2.6
#> 115 95 63.46 2.8
#> 116 NA 63.46 4.1
#> 117 95 63.46 3.1
#> 118 NA 33.22 2.5
#> 119 NA 33.22 2.7
#> 120 NA 33.22 2.6
#> 121 NA 63.46 2.1
#> 122 NA 63.46 2.0
#> 123 NA 63.46 1.7
#> 124 95 63.46 3.2
#> 125 NA 33.22 3.9
#> 126 75 63.46 2.6
#> 127 NA 33.22 4.9
#> 128 75 63.46 2.4
#> 129 188 83.00 3.3
#> 130 180 83.00 3.7
#> 131 185 83.00 3.9
#> 132 182 83.00 3.3
#> 133 188 83.00 3.2
#> 134 188 83.00 3.6
#> 135 180 83.00 3.8
#> 136 188 83.00 3.4
#> 137 188 83.00 3.9
#> 138 188 83.00 3.7
#> 139 182 83.00 3.7
#> 140 50 160.00 3.0
#> 141 50 160.00 3.2
#> 142 50 160.00 2.9
#> 143 50 160.00 3.3
#> 144 50 160.00 3.1
#> 145 50 160.00 3.8
#> 146 50 160.00 2.8
#> 147 50 160.00 2.7
#> 148 50 63.46 NA
#> 149 50 63.46 3.1
#> 150 NA 33.22 2.1
#> 151 NA 63.46 4.5
#> 152 NA 63.46 3.8
#> 153 NA 63.46 5.4
#> 154 NA 63.46 4.2
#> 155 NA 63.46 4.3
#> 156 NA 63.46 4.6
#> 157 NA 63.46 3.9
#> 158 NA 63.46 3.7
#> 159 NA 63.46 2.2
#> 160 NA 63.46 4.4
#> 161 NA 63.46 4.7
#> 162 NA 63.46 5.6
#> 163 NA 63.46 6.3
#> 164 NA 63.46 5.2
#> 165 NA 63.46 6.0
#> 166 NA 63.46 5.3
#> 167 NA 63.46 6.9
#> 168 NA 63.46 6.2
#> 169 NA 63.46 5.9
#> 170 NA 63.46 7.1
#> 171 NA 63.46 7.3
#> 172 NA 63.46 6.7
#> 173 NA 63.46 0.8
#> 174 NA 63.46 4.9
#> 175 NA 63.46 5.7
#> 176 75 63.46 3.5
# Hmm, Q1 has at least one of the RS or RSA variables as NAs. Will be difficult to standardize!
# Hope the correction factors are present in Ales conversion data
# Now calculate correction factors
hlcodL2 <- hlcodL2 %>% mutate(RS_x = 3/GroundSpeed,
Horizontal.opening..m. = Fishing.line*0.67,
Swep.one.side..after.formula...meter = 0.258819045*SweepLngt, # SIN(RADIANS(15))
Size.final..m = Horizontal.opening..m. + (Swep.one.side..after.formula...meter*2),
Swept.area = (Size.final..m*3*1860)/1000000,
RSA_x = 0.45388309675081/Swept.area)
hlfleL2 <- hlfleL2 %>% mutate(RS_x = 3/GroundSpeed,
Horizontal.opening..m. = Fishing.line*0.67,
Swep.one.side..after.formula...meter = 0.258819045*SweepLngt, # SIN(RADIANS(15))
Size.final..m = Horizontal.opening..m. + (Swep.one.side..after.formula...meter*2),
Swept.area = (Size.final..m*3*1860)/1000000,
RSA_x = 0.45388309675081/Swept.area)
# Check EQ. is correct by recalculating it in the sweep file
sweep <- sweep %>% mutate(Horizontal.opening..m.2 = Fishing.line*0.67,
Swep.one.side..after.formula...meter2 = 0.258819045*SweepLngt, # SIN(RADIANS(15))
Size.final..m2 = Horizontal.opening..m.2 + (Swep.one.side..after.formula...meter2*2),
Swept.area2 = (Size.final..m2*3*1860)/1000000,
RSA_x = 0.45388309675081/Swept.area2)
sweep %>%
drop_na() %>%
ggplot(., aes(as.numeric(RSA), RSA_x)) + geom_point() + geom_abline(intercept = 0, slope = 1)
# Yes it's the same
# Replace NAs with -1/3 (because ICES codes missing values as -9 and in the calculation above they get -1/3),
# so that I can filter them easily later
# sort(unique(hlcodL2$RS_x))
# sort(unique(hlcodL2$RSA_x))
hlcodL2$RS_x[is.na(hlcodL2$RS_x)] <- -1/3
hlcodL2$RS_sweep[is.na(hlcodL2$RS_sweep)] <- -1/3
hlcodL2$RSA_x[is.na(hlcodL2$RSA_x)] <- -1/3
hlcodL2$RSA_sweep[is.na(hlcodL2$RSA_sweep)] <- -1/3
hlfleL2$RS_x[is.na(hlfleL2$RS_x)] <- -1/3
hlfleL2$RS_sweep[is.na(hlfleL2$RS_sweep)] <- -1/3
hlfleL2$RSA_x[is.na(hlfleL2$RSA_x)] <- -1/3
hlfleL2$RSA_sweep[is.na(hlfleL2$RSA_sweep)] <- -1/3
# Compare the difference correction factors (calculated vs imported from sweep file)
p1 <- ggplot(filter(hlcodL2, RS_x > 0), aes(RS_x)) + geom_histogram() + xlim(0.4, 1.76)
p2 <- ggplot(hlcodL2, aes(RSA_x)) + geom_histogram()
p3 <- ggplot(hlcodL2, aes(RS_sweep)) + geom_histogram()
p4 <- ggplot(hlcodL2, aes(RSA_sweep)) + geom_histogram()
(p1 + p2) / (p3 + p4)
#> Warning: Removed 284 rows containing non-finite values (stat_bin).
#> Warning: Removed 2 rows containing missing values (geom_bar).
p5 <- ggplot(filter(hlfleL2, RS_x > 0), aes(RS_x)) + geom_histogram() + xlim(0.4, 1.76)
p6 <- ggplot(hlfleL2, aes(RSA_x)) + geom_histogram()
p7 <- ggplot(hlfleL2, aes(RS_sweep)) + geom_histogram()
p8 <- ggplot(hlfleL2, aes(RSA_sweep)) + geom_histogram()
(p5 + p6) / (p7 + p8)
#> Warning: Removed 115 rows containing non-finite values (stat_bin).
#> Warning: Removed 2 rows containing missing values (geom_bar).
# Why do I have RSA values smaller than one? (either because sweep length is longer or gear is larger (GOV))
# Check if I can calculate the same RSA in sweep as that entered there.
# Ok, so the equation is correct. Which ID's have RSA < 1?
hlcodL2 %>%
filter(RSA_x < 1 & RSA_x > 0) %>%
dplyr::select(Year, Country, Ship, Gear, haul.id, Horizontal.opening..m., Fishing.line,
Swep.one.side..after.formula...meter, SweepLngt, Size.final..m, Swept.area, RSA_x) %>%
ggplot(., aes(RSA_x, fill = factor(SweepLngt))) + geom_histogram() + facet_wrap(~Gear, ncol = 1)
# Check if I have more than one unique RS or RSA value per haul, or if it's "either this or that"
# Filter positive in both columns
hlcodL2 %>% filter(RS_x > 0 & RS_sweep > 0) %>% ggplot(., aes(RS_x, RS_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
hlcodL2 %>% filter(RSA_x > 0 & RSA_sweep > 0) %>% ggplot(., aes(RSA_x, RSA_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
hlfleL2 %>% filter(RS_x > 0 & RS_sweep > 0) %>% ggplot(., aes(RS_x, RS_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
hlfleL2 %>% filter(RSA_x > 0 & RSA_sweep > 0) %>% ggplot(., aes(RSA_x, RSA_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
# Ok, there's on odd RS_x that is larger than 3. It didn't catch anything and speed is 0.8! Will remove
hlcodL2 <- hlcodL2 %>% filter(RS_x < 3)
hlfleL2 <- hlfleL2 %>% filter(RS_x < 3)
# Plot again
hlcodL2 %>% filter(RS_x > 0 & RS_sweep > 0) %>% ggplot(., aes(RS_x, RS_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
hlfleL2 %>% filter(RS_x > 0 & RS_sweep > 0) %>% ggplot(., aes(RS_x, RS_sweep)) +
geom_point() + geom_abline(aes(intercept = 0, slope = 1), color = "red")
# They are largely the same when they overlap. When they differ, I will use RS_sweep
# Make a single RS and RSA column
# Cod
hlcodL3 <- hlcodL2 %>%
mutate(RS = -99,
RS = ifelse(RS_sweep > 0, RS_sweep, RS),
RS = ifelse(RS < 0 & RS_x > 0, RS_x, RS)) %>% # Note that there are no NA i RS_x. This replaces all non-RS_sweep values -0.3, so I can filter positive later
mutate(RSA = -99,
RSA = ifelse(RSA_sweep > 0, RSA_sweep, RSA),
RSA = ifelse(RSA < 0 & RSA_x > 0, RSA_x, RSA)) %>%
filter(RS > 0) %>%
filter(RSA > 0) %>%
mutate(RSRSA = RS*RSA)
# Plot
ggplot(hlcodL3, aes(RSRSA)) + geom_histogram()
hlfleL2 %>% filter(Country == "LAT") %>% distinct(Year) %>% arrange(Year)
#> # A tibble: 27 × 1
#> Year
#> <int>
#> 1 1991
#> 2 1993
#> 3 1995
#> 4 1996
#> 5 1997
#> 6 1999
#> 7 2000
#> 8 2001
#> 9 2002
#> 10 2003
#> # … with 17 more rows
# Flounder
hlfleL3 <- hlfleL2 %>%
mutate(RS = -999,
RS = ifelse(RS_sweep > 0, RS_sweep, RS),
RS = ifelse(RS < 0, RS_x, RS)) %>% # Note that there are no NA i RS_x. This replaces all non-RS_sweep values -0.3, so I can filter positive later
mutate(RSA = -999,
RSA = ifelse(RSA_sweep > 0, RSA_sweep, RSA),
RSA = ifelse(RSA < 0, RSA_x, RSA)) %>%
filter(RS > 0) %>%
filter(RSA > 0) %>%
mutate(RSRSA = RS*RSA)
# Test how many years of LAT data I miss out on because I can't standardize it.
# hlfleL2 %>%
# mutate(RS = -999,
# RS = ifelse(RS_sweep > 0, RS_sweep, RS),
# RS = ifelse(RS < 0, RS_x, RS)) %>% # Note that there are no NA i RS_x. This replaces all non-RS_sweep values -0.3, so I can filter positive later
# filter(RS > 0) %>%
# filter(Country == "LAT") %>%
# distinct(Year) %>%
# arrange(Year)
#
# hlfleL2 %>%
# mutate(RSA = -999,
# RSA = ifelse(RSA_sweep > 0, RSA_sweep, RSA),
# RSA = ifelse(RSA < 0, RSA_x, RSA)) %>%
# filter(RSA > 0) %>%
# filter(Country == "LAT") %>%
# distinct(Year) %>%
# arrange(Year)
# Plot
ggplot(hlcodL3, aes(RSRSA)) + geom_histogram()
# Standardize!
hlcodL3 <- hlcodL3 %>%
mutate(CPUEst_kg = CPUEun_kg*RS*RSA,
CPUEst = CPUEun*RS*RSA)
hlfleL3 <- hlfleL3 %>%
mutate(CPUEst_kg = CPUEun_kg*RS*RSA,
CPUEst = CPUEun*RS*RSA)
unique(is.na(hlcodL3$CPUEst_kg))
#> [1] FALSE
unique(is.na(hlcodL3$CPUEst))
#> [1] FALSE
min(hlcodL3$CPUEst_kg)
#> [1] 0
min(hlcodL3$CPUEst)
#> [1] 0
unique(is.na(hlfleL3$CPUEst_kg)) # Remove the few NA's here
#> [1] TRUE FALSE
hlfleL3 <- hlfleL3 %>% drop_na(CPUEst_kg)
unique(is.na(hlfleL3$CPUEst))
#> [1] FALSE
min(hlfleL3$CPUEst_kg)
#> [1] 0
min(hlfleL3$CPUEst)
#> [1] 0
# Now calculate total CPUE per haul in Orios unit, then create the new unit, i.e.:
# convert from kg of fish caught by trawling for 1 h a standard bottom swept area of
# 0.45km2 (using a TVL trawl with 75 m sweeps at the standard speed of three knots) to....
# kg of fish per km^2 by dividing with 0.45
hlcodhaul <- hlcodL3 %>%
group_by(haul.id) %>%
mutate(haul_cpue_kg = sum(CPUEst_kg),
haul_cpue = sum(CPUEst),
haul_cpue_kg_un = sum(CPUEun_kg),
haul_cpue_un = sum(CPUEun),
density = haul_cpue_kg/0.45,
density_ab = haul_cpue/0.45) %>%
ungroup() %>%
distinct(haul.id, .keep_all = TRUE)
# t <- hlcodhaul %>% filter(haul_cpue_un == 0)
# t <- hlcodhaul %>% filter(!Country == "SWE") %>% filter(haul_cpue_un > 0)
hlflehaul <- hlfleL3 %>%
group_by(haul.id) %>%
mutate(haul_cpue_kg = sum(CPUEst_kg),
haul_cpue = sum(CPUEst),
haul_cpue_kg_un = sum(CPUEun_kg),
haul_cpue_un = sum(CPUEun),
density = haul_cpue_kg/0.45,
density_ab = haul_cpue/0.45) %>%
ungroup() %>%
distinct(haul.id, .keep_all = TRUE)
# Rename things and select specific columns
dat <- hlcodhaul %>% rename("year" = "Year",
"lat" = "ShootLat",
"lon" = "ShootLong",
"quarter" = "Quarter",
"ices_rect" = "Rect") %>%
dplyr::select(density, year, lat, lon, quarter, haul.id, IDx, ices_rect, sub_div)
# Now add in the flounder data in the cod data based on haul ID
hlflehaul_select <- hlflehaul %>% mutate(density_fle = density) %>% dplyr::select(density_fle, haul.id)
dat <- left_join(dat, hlflehaul_select, by = "haul.id") %>% drop_na(density_fle)
dat %>% arrange(desc(density_fle)) %>% data.frame() %>% head(50)
#> density year lat lon quarter haul.id
#> 1 84.958409 2008 57.1850 20.6817 1 2008:1:LAT:BALL:TVL:1:4
#> 2 3107.363608 2008 56.2717 19.6533 1 2008:1:LAT:BALL:TVL:1:27
#> 3 45.808880 2007 56.9917 20.8033 1 2007:1:LAT:BALL:TVL:1:4
#> 4 74.676369 2010 57.3617 21.2350 4 2010:4:LAT:BALL:TVL:2:6
#> 5 295.261272 2012 56.5000 20.2150 1 2012:1:LAT:BALL:TVL:1:24
#> 6 102.464396 2011 56.9533 20.4150 1 2011:1:LAT:BALL:TVL:1:16
#> 7 242.575119 2008 57.2067 20.7283 1 2008:1:LAT:BALL:TVL:1:5
#> 8 13.872224 2010 57.2217 20.7167 1 2010:1:LAT:BALL:TVL:1:17
#> 9 51.843861 2007 55.7683 20.3333 1 2007:1:LAT:BALL:TVL:1:1
#> 10 95.664659 2007 57.2124 18.8491 4 2007:4:SWE:ARG:TVL:689:14
#> 11 6.508112 2009 57.8969 19.4288 1 2009:1:SWE:ARG:TVL:211:9
#> 12 6897.378835 2009 55.1083 19.7017 1 2009:1:RUS:ATL:TVL:57:4
#> 13 35.005848 2008 56.9350 20.3833 1 2008:1:LAT:BALL:TVL:1:1
#> 14 262.944923 2012 57.4600 21.2450 4 2012:4:LAT:BALL:TVL:2:6
#> 15 149.309819 2019 54.4500 19.3283 4 2019:4:POL:BAL:TVL:26256:4
#> 16 36.859878 2009 57.8994 19.4332 4 2009:4:SWE:ARG:TVL:723:11
#> 17 24.702776 2010 57.3550 20.5900 1 2010:1:LAT:BALL:TVL:1:15
#> 18 1153.634376 2014 55.4587 14.7253 1 2014:1:SWE:DAN2:TVL:48:26
#> 19 109.008774 2012 57.3683 21.2533 4 2012:4:LAT:BALL:TVL:2:7
#> 20 352.897387 2017 55.0233 16.3233 1 2017:1:POL:BAL:TVL:25066:28
#> 21 3499.177768 2011 55.3583 19.9267 1 2011:1:RUS:ATLD:TVL:56:40
#> 22 687.181689 2007 54.8692 15.4500 1 2007:1:POL:BAL:TVL:25159:31
#> 23 0.000000 2007 54.3692 19.2192 1 2007:1:POL:BAL:TVL:26001:35
#> 24 740.323341 2009 55.4950 20.0950 1 2009:1:RUS:ATL:TVL:57:10
#> 25 158.671747 1992 55.5833 15.8833 1 1992:1:GFR:SOL:CHP:25081:21
#> 26 31.348817 2001 57.1830 18.8793 1 2001:1:SWE:ARG:TVL:230:24
#> 27 3062.002553 2020 55.2367 17.3000 1 2020:1:POL:BAL:TVL:25463:9
#> 28 987.921853 2013 55.0750 19.6117 1 2013:1:RUS:ATLD:TVL:60:22
#> 29 53.784153 2007 56.5967 20.5100 1 2007:1:LAT:BALL:TVL:1:28
#> 30 4435.725757 2018 54.8317 19.6633 1 2018:1:RUS:ATL:TVL:67:2
#> 31 1838.109258 2001 56.4709 18.6149 4 2001:4:DEN:DAN2:TVL:93:38
#> 32 2176.245400 2020 55.2567 17.3700 1 2020:1:POL:BAL:TVL:25339:14
#> 33 62.375164 2020 54.4217 19.0267 1 2020:1:POL:BAL:TVL:26264:19
#> 34 181.453707 2008 57.1766 18.8081 4 2008:4:SWE:ARG:TVL:697:12
#> 35 883.537784 2019 55.4627 14.5290 4 2019:4:SWE:77SE:TVL:66:2
#> 36 1781.872489 2001 57.3537 19.1588 1 2001:1:SWE:ARG:TVL:236:29
#> 37 7210.671879 2014 55.4928 14.6408 1 2014:1:SWE:DAN2:TVL:51:27
#> 38 463.644551 2011 57.2433 21.0817 4 2011:4:LAT:BALL:TVL:2:11
#> 39 533.357067 1995 54.7667 15.6500 1 1995:1:GFR:SOL:H20:74:105
#> 40 274.848183 2001 55.0657 16.2425 1 2001:1:DEN:DAN2:TVL:81:39
#> 41 322.590582 2008 57.4733 21.1167 4 2008:4:LAT:BALL:TVL:2:3
#> 42 417.838920 2001 55.0489 16.2850 1 2001:1:DEN:DAN2:TVL:79:38
#> 43 511.328391 2016 54.7683 15.3100 1 2016:1:POL:BAL:TVL:25177:12
#> 44 24.325399 2007 57.2217 20.7467 1 2007:1:LAT:BALL:TVL:1:18
#> 45 22.230389 2011 57.0000 20.8117 1 2011:1:LAT:BALL:TVL:1:7
#> 46 1111.835196 2002 54.8461 15.3151 1 2002:1:DEN:DAN2:TVL:32:18
#> 47 1.255573 2008 57.0667 20.6367 1 2008:1:LAT:BALL:TVL:1:16
#> 48 9.415983 2013 57.7022 19.1408 4 2013:4:SWE:DAN2:TVL:33:17
#> 49 1642.707733 2007 57.2033 20.7167 4 2007:4:LAT:BALL:TVL:2:9
#> 50 1335.057913 2010 54.8850 18.8750 1 2010:1:POL:BAL:TVL:26087:33
#> IDx ices_rect sub_div density_fle
#> 1 2008.1.LAT.67BC.TVL.1.4 43H0 28 11169.594
#> 2 2008.1.LAT.67BC.TVL.1.27 41G9 26 9046.180
#> 3 2007.1.LAT.67BC.TVL.1.4 42H0 28 6636.965
#> 4 2010.4.LAT.67BC.TVL.2.6 43H1 28 6434.487
#> 5 2012.1.LAT.67BC.TVL.1.24 42H0 28 5782.487
#> 6 2011.1.LAT.67BC.TVL.1.16 42H0 28 5327.548
#> 7 2008.1.LAT.67BC.TVL.1.5 43H0 28 4178.697
#> 8 2010.1.LAT.67BC.TVL.1.17 43H0 28 3942.139
#> 9 2007.1.LAT.67BC.TVL.1.1 40H0 26 3200.816
#> 10 2007.4.SWE.77AR.TVL.689.14 43G8 28 3196.460
#> 11 2009.1.SWE.77AR.TVL.211.9 44G9 28 2807.984
#> 12 2009.1.RUS.RUNT.TVL.57.4 39G9 26 2712.294
#> 13 2008.1.LAT.67BC.TVL.1.1 42H0 28 2707.929
#> 14 2012.4.LAT.67BC.TVL.2.6 43H1 28 2680.423
#> 15 2019.4.POL.67BC.TVL.26256.4 37G9 26 2505.173
#> 16 2009.4.SWE.77AR.TVL.723.11 44G9 28 2481.592
#> 17 2010.1.LAT.67BC.TVL.1.15 43H0 28 2447.802
#> 18 2014.1.SWE.26D4.TVL.48.26 39G4 24 2442.102
#> 19 2012.4.LAT.67BC.TVL.2.7 43H1 28 2424.936
#> 20 2017.1.POL.67BC.TVL.25066.28 39G6 25 2416.610
#> 21 2011.1.RUS.RUJB.TVL.56.40 39G9 26 2415.328
#> 22 2007.1.POL.67BC.TVL.25159.31 38G5 25 2381.793
#> 23 2007.1.POL.67BC.TVL.26001.35 37G9 26 2357.677
#> 24 2009.1.RUS.RUNT.TVL.57.10 39H0 26 2341.579
#> 25 1992.1.GFR.06S1.CHP.25081.21 40G5 25 2286.580
#> 26 2001.1.SWE.77AR.TVL.230.24 43G8 28 2207.518
#> 27 2020.1.POL.67BC.TVL.25463.9 39G7 25 2206.927
#> 28 2013.1.RUS.RUJB.TVL.60.22 39G9 26 2188.610
#> 29 2007.1.LAT.67BC.TVL.1.28 42H0 28 2144.123
#> 30 2018.1.RUS.RUNT.TVL.67.2 38G9 26 2128.009
#> 31 2001.4.DEN.26D4.TVL.93.38 41G8 26 2098.998
#> 32 2020.1.POL.67BC.TVL.25339.14 39G7 25 2070.693
#> 33 2020.1.POL.67BC.TVL.26264.19 37G9 26 2063.225
#> 34 2008.4.SWE.77AR.TVL.697.12 43G8 28 2048.861
#> 35 2019.4.SWE.77SE.TVL.66.2 39G4 24 2038.147
#> 36 2001.1.SWE.77AR.TVL.236.29 43G9 28 2019.608
#> 37 2014.1.SWE.26D4.TVL.51.27 39G4 24 1999.449
#> 38 2011.4.LAT.67BC.TVL.2.11 43H1 28 1996.229
#> 39 1995.1.GFR.06S1.H20.74.105 38G5 25 1963.572
#> 40 2001.1.DEN.26D4.TVL.81.39 39G6 25 1909.892
#> 41 2008.4.LAT.67BC.TVL.2.3 43H1 28 1893.857
#> 42 2001.1.DEN.26D4.TVL.79.38 39G6 25 1870.911
#> 43 2016.1.POL.67BC.TVL.25177.12 38G5 25 1869.831
#> 44 2007.1.LAT.67BC.TVL.1.18 43H0 28 1829.415
#> 45 2011.1.LAT.67BC.TVL.1.7 43H0 28 1796.272
#> 46 2002.1.DEN.26D4.TVL.32.18 38G5 25 1765.521
#> 47 2008.1.LAT.67BC.TVL.1.16 43H0 28 1757.879
#> 48 2013.4.SWE.26D4.TVL.33.17 44G9 28 1696.887
#> 49 2007.4.LAT.67BC.TVL.2.9 43H0 28 1695.008
#> 50 2010.1.POL.67BC.TVL.26087.33 38G8 26 1692.796
# Filter unrealistically large densities
dat <- dat %>% filter(density_fle < 10000)
ggplot(dat, aes(density, density_fle)) + geom_point()
Compare cod data with Orio et al (2017)
# Read Orio data first for comparison:
test_cod <- hlcodhaul %>% filter(!Country == "SWE")
test_fle <- hlflehaul %>% filter(!Country == "SWE")
orio_cod <- read.csv("/Users/maxlindmark/Desktop/R_STUDIO_PROJECTS/ale_gear_standardization/datras_st_ale.csv")
orio_fle <- read.csv("/Users/maxlindmark/Desktop/R_STUDIO_PROJECTS/ale_gear_standardization/datras_fle_st_ale.csv")
orio_cod <- orio_cod %>%
group_by(IDX) %>%
mutate(haul_cpue_kg = sum(CPUEstBIOyear),
haul_cpue = sum(CPUEst),
haul_cpue_kg_un = sum(CPUEunBIOyear),
haul_cpue_un = sum(CPUEun)) %>%
ungroup() %>%
distinct(IDX, .keep_all = TRUE)
orio_fle <- orio_fle %>%
group_by(IDX) %>%
mutate(haul_cpue_kg = sum(CPUEstBIOyear),
haul_cpue = sum(CPUEst),
haul_cpue_kg_un = sum(CPUEunBIOyear),
haul_cpue_un = sum(CPUEun)) %>%
ungroup() %>%
distinct(IDX, .keep_all = TRUE)
# hlcodhaul %>% group_by(IDx) %>% mutate(n = n()) %>% ungroup() %>% distinct(n)
# Standardize data for easier plotting
test_cod_q1 <- test_cod %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, Year, Ship3, Country, Gear, Quarter) %>%
mutate(source = "Max",
species = "Cod") %>%
rename("Ship" = "Ship3") %>%
filter(Year > 1992 & Year < 2017 & Quarter == 1)
test_cod_q4 <- test_cod %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, Year, Ship3, Country, Gear, Quarter) %>%
mutate(source = "Max",
species = "Cod") %>%
rename("Ship" = "Ship3") %>%
filter(Year > 1992 & Year < 2017 & Quarter == 4)
test_fle_q1 <- test_fle %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, Year, Ship3, Country, Gear, Quarter) %>%
mutate(source = "Max",
species = "Fle") %>%
rename("Ship" = "Ship3") %>%
filter(Year > 1992 & Year < 2017 & Quarter == 1)
test_fle_q4 <- test_fle %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, Year, Ship3, Country, Gear, Quarter) %>%
mutate(source = "Max",
species = "Fle") %>%
rename("Ship" = "Ship3") %>%
filter(Year > 1992 & Year < 2017 & Quarter == 4)
orio_cod_q1 <- orio_cod %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, year, vessel, IDX) %>%
mutate(source = "Ale",
species = "Cod") %>%
rename("Year" = "year",
"Ship" = "vessel") %>%
mutate(IDX2 = IDX,
IDX3 = IDX) %>%
separate(IDX, sep = c(5:7), into = c("temp_year", "Quarter")) %>%
separate(temp_year, sep = c(4:5), into = c("Year", "scrap")) %>%
separate(IDX2, sep = 7, into = c("scrap2", "Country")) %>%
separate(Country, sep = 3, into = c("Country", "scrap3")) %>%
separate(IDX3, sep = 15, into = c("scrap4", "Gear")) %>%
separate(Gear, sep = 3, into = c("Gear", "scrap5")) %>%
dplyr::select(-scrap, -scrap2, -scrap3, -scrap4, -scrap5) %>%
filter(Quarter == 1) %>%
mutate(Year = as.integer(Year),
Quarter = as.integer(Quarter)) %>%
mutate(haul_cpue_kg = haul_cpue_kg/1000,
haul_cpue_kg_un = haul_cpue_kg_un/1000) %>%
filter(Year > 1992) %>%
filter(Country %in% unique(test_cod$Country))
orio_cod_q4 <- orio_cod %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, year, vessel, IDX) %>%
mutate(source = "Ale",
species = "Cod") %>%
rename("Year" = "year",
"Ship" = "vessel") %>%
mutate(IDX2 = IDX,
IDX3 = IDX) %>%
separate(IDX, sep = c(5:7), into = c("temp_year", "Quarter")) %>%
separate(temp_year, sep = c(4:5), into = c("Year", "scrap")) %>%
separate(IDX2, sep = 7, into = c("scrap2", "Country")) %>%
separate(Country, sep = 3, into = c("Country", "scrap3")) %>%
separate(IDX3, sep = 15, into = c("scrap4", "Gear")) %>%
separate(Gear, sep = 3, into = c("Gear", "scrap5")) %>%
dplyr::select(-scrap, -scrap2, -scrap3, -scrap4, -scrap5) %>%
filter(Quarter == 4) %>%
mutate(Year = as.integer(Year),
Quarter = as.integer(Quarter)) %>%
mutate(haul_cpue_kg = haul_cpue_kg/1000,
haul_cpue_kg_un = haul_cpue_kg_un/1000) %>%
filter(Year > 1992) %>%
filter(Country %in% unique(test_cod$Country))
orio_fle_q1 <- orio_fle %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, year, vessel, IDX) %>%
mutate(source = "Ale",
species = "Fle") %>%
rename("Year" = "year",
"Ship" = "vessel") %>%
mutate(IDX2 = IDX,
IDX3 = IDX) %>%
separate(IDX, sep = c(5:7), into = c("temp_year", "Quarter")) %>%
separate(temp_year, sep = c(4:5), into = c("Year", "scrap")) %>%
separate(IDX2, sep = 7, into = c("scrap2", "Country")) %>%
separate(Country, sep = 3, into = c("Country", "scrap3")) %>%
separate(IDX3, sep = 15, into = c("scrap4", "Gear")) %>%
separate(Gear, sep = 3, into = c("Gear", "scrap5")) %>%
dplyr::select(-scrap, -scrap2, -scrap3, -scrap4, -scrap5) %>%
filter(Quarter == 1) %>%
mutate(Year = as.integer(Year),
Quarter = as.integer(Quarter)) %>%
mutate(haul_cpue_kg = haul_cpue_kg/1000,
haul_cpue_kg_un = haul_cpue_kg_un/1000) %>%
filter(Year > 1992) %>%
filter(Country %in% unique(test_cod$Country))
orio_fle_q4 <- orio_fle %>%
dplyr::select(haul_cpue_kg, haul_cpue, haul_cpue_kg_un, haul_cpue_un, year, vessel, IDX) %>%
mutate(source = "Ale",
species = "Fle") %>%
rename("Year" = "year",
"Ship" = "vessel") %>%
mutate(IDX2 = IDX,
IDX3 = IDX) %>%
separate(IDX, sep = c(5:7), into = c("temp_year", "Quarter")) %>%
separate(temp_year, sep = c(4:5), into = c("Year", "scrap")) %>%
separate(IDX2, sep = 7, into = c("scrap2", "Country")) %>%
separate(Country, sep = 3, into = c("Country", "scrap3")) %>%
separate(IDX3, sep = 15, into = c("scrap4", "Gear")) %>%
separate(Gear, sep = 3, into = c("Gear", "scrap5")) %>%
dplyr::select(-scrap, -scrap2, -scrap3, -scrap4, -scrap5) %>%
filter(Quarter == 4) %>%
mutate(Year = as.integer(Year),
Quarter = as.integer(Quarter)) %>%
mutate(haul_cpue_kg = haul_cpue_kg/1000,
haul_cpue_kg_un = haul_cpue_kg_un/1000) %>%
filter(Year > 1992) %>%
filter(Country %in% unique(test_cod$Country))
sort(unique(test_cod_q1$Country))
#> [1] "DEN" "GFR" "LAT" "LTU" "POL" "RUS"
sort(unique(orio_cod_q1$Country))
#> [1] "DEN" "GFR" "LAT" "LTU" "POL" "RUS"
# Check proportions of zero
t <- test_cod_q1 %>% filter(haul_cpue_kg > 0)
t <- orio_cod_q1 %>% filter(haul_cpue_kg > 0)
t <- test_cod_q4 %>% filter(haul_cpue_kg > 0)
t <- orio_cod_q4 %>% filter(haul_cpue_kg > 0)
t <- test_fle_q1 %>% filter(haul_cpue_kg > 0)
t <- orio_fle_q1 %>% filter(haul_cpue_kg > 0)
t <- test_fle_q4 %>% filter(haul_cpue_kg > 0)
t <- orio_fle_q4 %>% filter(haul_cpue_kg > 0)
test_full <- bind_rows(orio_fle_q1, orio_fle_q4, orio_cod_q1, orio_cod_q4,
test_cod_q1, test_cod_q4, test_fle_q1, test_fle_q4)
# Check the non-standardized data for cod
# Raw abundance cpue
test_full %>%
filter(species == "Cod") %>%
ggplot(., aes(factor(Year), haul_cpue_un, color = source)) +
geom_point(size = 1, position = position_dodge(width = 0.5)) +
theme(axis.text.x = element_text(angle = 90)) +
facet_wrap(~Quarter) +
NULL
test_full %>%
filter(species == "Cod" & Quarter == 1) %>%
ggplot(., aes(haul_cpue_un, fill = source)) +
geom_histogram(position = position_dodge()) +
facet_wrap(~Year, scale = "free") +
theme(axis.text.x = element_text(angle = 90)) +
NULL
test_full %>%
filter(species == "Cod" & Quarter == 4) %>%
ggplot(., aes(haul_cpue_un, fill = source)) +
geom_histogram(position = position_dodge()) +
facet_wrap(~Year, scale = "free") +
theme(axis.text.x = element_text(angle = 90)) +
NULL
# Mean abundance cpue
test_full %>%
filter(species == "Cod") %>%
group_by(Year, Quarter, source) %>%
summarise(mean_cpue = mean(haul_cpue_un),
sd_cpue = sd(haul_cpue_un)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
geom_point(size = 3) +
facet_wrap(~Quarter, ncol = 1) +
NULL
# Mean abundance cpue by country
test_full %>%
filter(species == "Cod") %>%
group_by(Year, source, Quarter, Country) %>%
summarise(mean_cpue = mean(haul_cpue_un),
sd_cpue = sd(haul_cpue_un)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
facet_grid(Quarter ~ Country) +
NULL
# Mean abundance cpue for non-zero cathes
test_full %>%
filter(species == "Cod") %>%
filter(haul_cpue_un > 0) %>%
group_by(Year, Quarter, source) %>%
summarise(mean_cpue = mean(haul_cpue_un),
sd_cpue = sd(haul_cpue_un)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
geom_point(size = 3) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Now plot corrected biomass cpue
test_full %>%
filter(species == "Cod") %>%
ggplot(., aes(factor(Year), haul_cpue_kg, color = source)) +
geom_point(size = 1, position = position_dodge(width = 0.5)) +
theme(axis.text.x = element_text(angle = 90)) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Mean corrected biomass cpue
test_full %>%
filter(species == "Cod") %>%
group_by(Year, Quarter, source) %>%
summarise(mean_cpue = mean(haul_cpue_kg),
sd_cpue = sd(haul_cpue_kg)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
geom_point(size = 3) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Now check in on flounder
# Raw abundance cpue
test_full %>%
filter(species == "Fle") %>%
ggplot(., aes(factor(Year), haul_cpue_un, color = source)) +
geom_point(size = 1, position = position_dodge(width = 0.5)) +
theme(axis.text.x = element_text(angle = 90)) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
test_full %>%
filter(species == "Fle" & Quarter == 1) %>%
ggplot(., aes(haul_cpue_un, fill = source)) +
geom_histogram(position = position_dodge()) +
facet_wrap(~Year, scale = "free") +
theme(axis.text.x = element_text(angle = 90)) +
NULL
test_full %>%
filter(species == "Fle" & Quarter == 4) %>%
ggplot(., aes(haul_cpue_un, fill = source)) +
geom_histogram(position = position_dodge()) +
facet_wrap(~Year, scale = "free") +
theme(axis.text.x = element_text(angle = 90)) +
NULL
# Mean abundance cpue
test_full %>%
filter(species == "Fle") %>%
group_by(Year, Quarter, source) %>%
summarise(mean_cpue = mean(haul_cpue_un),
sd_cpue = sd(haul_cpue_un)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
geom_point(size = 3) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Ok, here we can see that Ale predicts an increase earlier, which we also saw
# on the plot of raw catches as points
# Mean abundance cpue by country to see how this can arise
test_full %>%
filter(species == "Fle") %>%
group_by(Year, Quarter, source, Country) %>%
summarise(mean_cpue = mean(haul_cpue_un),
sd_cpue = sd(haul_cpue_un)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
facet_grid(Quarter ~ Country) +
NULL
# Ok, after checking, the reason I don't have the older LAT data is because I don't
# have RS or RSA-values for those hauls, even though the catch data are in datras...
# Should probably check with Ale how he corrected those!
# Now plot corrected biomass cpue
test_full %>%
filter(species == "Fle") %>%
ggplot(., aes(factor(Year), haul_cpue_kg, color = source)) +
geom_point(size = 1, position = position_dodge(width = 0.5)) +
theme(axis.text.x = element_text(angle = 90)) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Mean corrected biomass cpue
test_full %>%
filter(species == "Fle") %>%
group_by(Year, Quarter, source) %>%
summarise(mean_cpue = mean(haul_cpue_kg),
sd_cpue = sd(haul_cpue_kg)) %>%
ggplot(., aes(Year, mean_cpue, linetype = source, color = source)) +
geom_line(size = 1.1) +
geom_point(size = 3) +
facet_wrap(~ Quarter, ncol = 1) +
NULL
# Then check length-weight relationships againAdd in the environmental variables
Depth
# Read the tifs
west <- raster("data/depth_geo_tif/D5_2018_rgb-1.tif")
#plot(west)
east <- raster("data/depth_geo_tif/D6_2018_rgb-1.tif")
# plot(east)
dep_rast <- raster::merge(west, east)
dat$depth <- extract(dep_rast, dat[, 4:3])
# Convert to depth (instead of elevation)
ggplot(dat, aes(depth)) + geom_histogram()
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
dat$depth <- (dat$depth - max(drop_na(dat)$depth)) *-1
#> drop_na: no rows removed
ggplot(dat, aes(depth)) + geom_histogram()
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Oxygen
# Rename fishdata to fishdat so that I don't overwrite anything. Not all years in the BITS
# have environmental data, and I don't want to loose important trawl information
fishdat <- dat
# Downloaded from here: https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=BALTICSEA_REANALYSIS_BIO_003_012
# Extract raster points: https://gisday.wordpress.com/2014/03/24/extract-raster-values-from-points-using-r/comment-page-1/
# https://rpubs.com/boyerag/297592
# https://pjbartlein.github.io/REarthSysSci/netCDF.html#get-a-variable
# Open the netCDF file
ncin <- nc_open("data/NEMO_Nordic_SCOBI/dataset-reanalysis-scobi-monthlymeans_1610091357600.nc")
print(ncin)
#> File data/NEMO_Nordic_SCOBI/dataset-reanalysis-scobi-monthlymeans_1610091357600.nc (NC_FORMAT_CLASSIC):
#>
#> 1 variables (excluding dimension variables):
#> float o2b[longitude,latitude,time]
#> long_name: Sea_floor_Dissolved_Oxygen_Concentration
#> missing_value: NaN
#> standard_name: mole_concentration_of_dissolved_molecular_oxygen_in_sea_water
#> units: mmol m-3
#> _FillValue: NaN
#> _ChunkSizes: 1
#> _ChunkSizes: 523
#> _ChunkSizes: 383
#>
#> 3 dimensions:
#> time Size:324
#> axis: T
#> long_name: Validity time
#> standard_name: time
#> units: days since 1950-01-01 00:00:00
#> calendar: gregorian
#> _ChunkSizes: 512
#> _CoordinateAxisType: Time
#> valid_min: 15721.5
#> valid_max: 25551.5
#> latitude Size:166
#> axis: Y
#> standard_name: latitude
#> long_name: latitude
#> units: degrees_north
#> _CoordinateAxisType: Lat
#> valid_min: 52.991626739502
#> valid_max: 58.4915390014648
#> longitude Size:253
#> standard_name: longitude
#> long_name: longitude
#> units: degrees_east
#> axis: X
#> _CoordinateAxisType: Lon
#> valid_min: 9.01375484466553
#> valid_max: 23.013614654541
#>
#> 24 global attributes:
#> references: http://www.smhi.se
#> institution: Swedish Meterological and Hydrological Institute
#> history: See source and creation_date attributees
#> Conventions: CF-1.5
#> contact: servicedesk_cmems@mercator-ocean.eu
#> comment: Provided by SMHI as a Copernicus Marine Environment Monitoring Service production unit
#> bullentin_type: reanalysis
#> cmems_product_id: BALTICSEA_REANALYSIS_BIO_003_012
#> title: CMEMS V4 Reanalysis: SCOBI model 3D fields (monthly means)
#> FROM_ORIGINAL_FILE__easternmost_longitude: 30.2357654571533
#> FROM_ORIGINAL_FILE__northernmost_latitude: 65.8914184570312
#> FROM_ORIGINAL_FILE__westernmost_longitude: 9.01375484466553
#> FROM_ORIGINAL_FILE__southernmost_latitude: 48.49169921875
#> shallowest_depth: 1.50136542320251
#> deepest_depth: 711.059204101562
#> source: SMHI reanalysis run NORDIC-NS2_1d_20191201_20191202
#> file_quality_index: 1
#> creation_date: 2020-11-16 UTC
#> bullentin_date: 20191201
#> start_date: 2019-12-01 UTC
#> stop_date: 2019-12-01 UTC
#> start_time: 00:00 UTC
#> stop_time: 00:00 UTC
#> _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention
# Get longitude and latitude
lon <- ncvar_get(ncin,"longitude")
nlon <- dim(lon)
head(lon)
#> [1] 9.013755 9.069310 9.124865 9.180420 9.235975 9.291530
lat <- ncvar_get(ncin,"latitude")
nlat <- dim(lat)
head(lat)
#> [1] 52.99163 53.02496 53.05829 53.09163 53.12496 53.15829
# Get time
time <- ncvar_get(ncin,"time")
time
#> [1] 15721.5 15751.0 15780.5 15811.0 15841.5 15872.0 15902.5 15933.5 15964.0
#> [10] 15994.5 16025.0 16055.5 16086.5 16116.0 16145.5 16176.0 16206.5 16237.0
#> [19] 16267.5 16298.5 16329.0 16359.5 16390.0 16420.5 16451.5 16481.0 16510.5
#> [28] 16541.0 16571.5 16602.0 16632.5 16663.5 16694.0 16724.5 16755.0 16785.5
#> [37] 16816.5 16846.5 16876.5 16907.0 16937.5 16968.0 16998.5 17029.5 17060.0
#> [46] 17090.5 17121.0 17151.5 17182.5 17212.0 17241.5 17272.0 17302.5 17333.0
#> [55] 17363.5 17394.5 17425.0 17455.5 17486.0 17516.5 17547.5 17577.0 17606.5
#> [64] 17637.0 17667.5 17698.0 17728.5 17759.5 17790.0 17820.5 17851.0 17881.5
#> [73] 17912.5 17942.0 17971.5 18002.0 18032.5 18063.0 18093.5 18124.5 18155.0
#> [82] 18185.5 18216.0 18246.5 18277.5 18307.5 18337.5 18368.0 18398.5 18429.0
#> [91] 18459.5 18490.5 18521.0 18551.5 18582.0 18612.5 18643.5 18673.0 18702.5
#> [100] 18733.0 18763.5 18794.0 18824.5 18855.5 18886.0 18916.5 18947.0 18977.5
#> [109] 19008.5 19038.0 19067.5 19098.0 19128.5 19159.0 19189.5 19220.5 19251.0
#> [118] 19281.5 19312.0 19342.5 19373.5 19403.0 19432.5 19463.0 19493.5 19524.0
#> [127] 19554.5 19585.5 19616.0 19646.5 19677.0 19707.5 19738.5 19768.5 19798.5
#> [136] 19829.0 19859.5 19890.0 19920.5 19951.5 19982.0 20012.5 20043.0 20073.5
#> [145] 20104.5 20134.0 20163.5 20194.0 20224.5 20255.0 20285.5 20316.5 20347.0
#> [154] 20377.5 20408.0 20438.5 20469.5 20499.0 20528.5 20559.0 20589.5 20620.0
#> [163] 20650.5 20681.5 20712.0 20742.5 20773.0 20803.5 20834.5 20864.0 20893.5
#> [172] 20924.0 20954.5 20985.0 21015.5 21046.5 21077.0 21107.5 21138.0 21168.5
#> [181] 21199.5 21229.5 21259.5 21290.0 21320.5 21351.0 21381.5 21412.5 21443.0
#> [190] 21473.5 21504.0 21534.5 21565.5 21595.0 21624.5 21655.0 21685.5 21716.0
#> [199] 21746.5 21777.5 21808.0 21838.5 21869.0 21899.5 21930.5 21960.0 21989.5
#> [208] 22020.0 22050.5 22081.0 22111.5 22142.5 22173.0 22203.5 22234.0 22264.5
#> [217] 22295.5 22325.0 22354.5 22385.0 22415.5 22446.0 22476.5 22507.5 22538.0
#> [226] 22568.5 22599.0 22629.5 22660.5 22690.5 22720.5 22751.0 22781.5 22812.0
#> [235] 22842.5 22873.5 22904.0 22934.5 22965.0 22995.5 23026.5 23056.0 23085.5
#> [244] 23116.0 23146.5 23177.0 23207.5 23238.5 23269.0 23299.5 23330.0 23360.5
#> [253] 23391.5 23421.0 23450.5 23481.0 23511.5 23542.0 23572.5 23603.5 23634.0
#> [262] 23664.5 23695.0 23725.5 23756.5 23786.0 23815.5 23846.0 23876.5 23907.0
#> [271] 23937.5 23968.5 23999.0 24029.5 24060.0 24090.5 24121.5 24151.5 24181.5
#> [280] 24212.0 24242.5 24273.0 24303.5 24334.5 24365.0 24395.5 24426.0 24456.5
#> [289] 24487.5 24517.0 24546.5 24577.0 24607.5 24638.0 24668.5 24699.5 24730.0
#> [298] 24760.5 24791.0 24821.5 24852.5 24882.0 24911.5 24942.0 24972.5 25003.0
#> [307] 25033.5 25064.5 25095.0 25125.5 25156.0 25186.5 25217.5 25247.0 25276.5
#> [316] 25307.0 25337.5 25368.0 25398.5 25429.5 25460.0 25490.5 25521.0 25551.5
tunits <- ncatt_get(ncin,"time","units")
nt <- dim(time)
nt
#> [1] 324
tunits
#> $hasatt
#> [1] TRUE
#>
#> $value
#> [1] "days since 1950-01-01 00:00:00"
# Get oxygen
dname <- "o2b"
oxy_array <- ncvar_get(ncin,dname)
dlname <- ncatt_get(ncin,dname,"long_name")
dunits <- ncatt_get(ncin,dname,"units")
fillvalue <- ncatt_get(ncin,dname,"_FillValue")
dim(oxy_array)
#> [1] 253 166 324
# Get global attributes
title <- ncatt_get(ncin,0,"title")
institution <- ncatt_get(ncin,0,"institution")
datasource <- ncatt_get(ncin,0,"source")
references <- ncatt_get(ncin,0,"references")
history <- ncatt_get(ncin,0,"history")
Conventions <- ncatt_get(ncin,0,"Conventions")
# Convert time: split the time units string into fields
tustr <- strsplit(tunits$value, " ")
tdstr <- strsplit(unlist(tustr)[3], "-")
tmonth <- as.integer(unlist(tdstr)[2])
tday <- as.integer(unlist(tdstr)[3])
tyear <- as.integer(unlist(tdstr)[1])
# Here I deviate from the guide a little bit. Save this info:
dates <- chron(time, origin = c(tmonth, tday, tyear))
# Crop the date variable
months <- as.numeric(substr(dates, 2, 3))
years <- as.numeric(substr(dates, 8, 9))
years <- ifelse(years > 90, 1900 + years, 2000 + years)
# Replace netCDF fill values with NA's
oxy_array[oxy_array == fillvalue$value] <- NA
# Next, we need to work with the months that correspond to the quarters that we use.
# loop through each time step, and if it is a good month save it as a raster.
# First get the index of months that correspond to Q4
months
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1
#> [26] 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2
#> [51] 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
#> [76] 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
#> [101] 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5
#> [126] 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
#> [151] 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7
#> [176] 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8
#> [201] 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9
#> [226] 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10
#> [251] 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11
#> [276] 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
#> [301] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
index_keep_q1 <- which(months < 4)
index_keep_q4 <- which(months > 9)
oxy_q1 <- oxy_array[, , index_keep_q1]
oxy_q4 <- oxy_array[, , index_keep_q4]
months_keep_q1 <- months[index_keep_q1]
months_keep_q4 <- months[index_keep_q4]
years_keep_q1 <- years[index_keep_q1]
years_keep_q4 <- years[index_keep_q4]
# Now we have an array with only Q4 data...
# We need to now calculate the average within a year.
# Get a sequence that takes every third value between 1: number of months (length)
loop_seq_q1 <- seq(1, dim(oxy_q1)[3], by = 3)
loop_seq_q4 <- seq(1, dim(oxy_q4)[3], by = 3)
# Create objects that will hold data
dlist_q1 <- list()
dlist_q4 <- list()
oxy_1 <- c()
oxy_2 <- c()
oxy_3 <- c()
oxy_ave_q1 <- c()
oxy_10 <- c()
oxy_11 <- c()
oxy_12 <- c()
oxy_ave_q4 <- c()
# Now average by quarter. The vector loop_seq_q1 is 1, 4, 7 etc. So first i is 1, 2, 3,
# which is the index we want.
for(i in loop_seq_q1) { # We can use q1 as looping index, doesn't matter!
oxy_1 <- oxy_q1[, , (i)]
oxy_2 <- oxy_q1[, , (i + 1)]
oxy_3 <- oxy_q1[, , (i + 2)]
oxy_10 <- oxy_q4[, , (i)]
oxy_11 <- oxy_q4[, , (i + 1)]
oxy_12 <- oxy_q4[, , (i + 2)]
oxy_ave_q1 <- (oxy_1 + oxy_2 + oxy_3) / 3
oxy_ave_q4 <- (oxy_10 + oxy_11 + oxy_12) / 3
list_pos_q1 <- ((i/3) - (1/3)) + 1 # to get index 1:n(years)
list_pos_q4 <- ((i/3) - (1/3)) + 1 # to get index 1:n(years)
dlist_q1[[list_pos_q1]] <- oxy_ave_q1
dlist_q4[[list_pos_q4]] <- oxy_ave_q4
}
# Now name the lists with the year:
names(dlist_q1) <- unique(years_keep_q1)
names(dlist_q4) <- unique(years_keep_q4)
# Now I need to make a loop where I extract the raster value for each year...
# The cpue data is called dat so far in this script
# Filter years in the cpue data frame to only have the years I have oxygen for
# Note: I will append the most recent data in the end, event though we don't have
# environmental data for it
d_sub_oxy_q1 <- dat %>% filter(quarter == 1) %>% filter(year %in% names(dlist_q1)) %>% droplevels()
#> filter: removed 3,586 rows (40%), 5,353 rows remaining
#> filter: removed 209 rows (4%), 5,144 rows remaining
d_sub_oxy_q4 <- dat %>% filter(quarter == 4) %>% filter(year %in% names(dlist_q4)) %>% droplevels()
#> filter: removed 5,353 rows (60%), 3,586 rows remaining
#> filter: removed 133 rows (4%), 3,453 rows remaining
# Create data holding object
data_list_q1 <- list()
data_list_q4 <- list()
# ... And for the oxygen raster
raster_list_q1 <- list()
raster_list_q4 <- list()
# Create factor year for indexing the list in the loop
d_sub_oxy_q1$year_f <- as.factor(d_sub_oxy_q1$year)
d_sub_oxy_q4$year_f <- as.factor(d_sub_oxy_q4$year)
# Loop through each year and extract raster values for the cpue data points
for(i in unique(d_sub_oxy_q1$year_f)) { # We can use q1 as looping index, doesn't matter!
# Set plot limits
ymin = 54; ymax = 58; xmin = 12; xmax = 22
# Subset a year
oxy_slice_q1 <- dlist_q1[[i]]
oxy_slice_q4 <- dlist_q4[[i]]
# Create raster for that year (i)
r_q1 <- raster(t(oxy_slice_q1), xmn = min(lon), xmx = max(lon), ymn = min(lat), ymx = max(lat),
crs = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs+ towgs84=0,0,0"))
r_q4 <- raster(t(oxy_slice_q4), xmn = min(lon), xmx = max(lon), ymn = min(lat), ymx = max(lat),
crs = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs+ towgs84=0,0,0"))
# Flip...
r_q1 <- flip(r_q1, direction = 'y')
r_q4 <- flip(r_q4, direction = 'y')
plot(r_q1, main = i)
plot(r_q4, main = i)
# Filter the same year (i) in the cpue data and select only coordinates
d_slice_q1 <- d_sub_oxy_q1 %>% filter(year_f == i) %>% dplyr::select(lon, lat)
d_slice_q4 <- d_sub_oxy_q4 %>% filter(year_f == i) %>% dplyr::select(lon, lat)
# Make into a SpatialPoints object
data_sp_q1 <- SpatialPoints(d_slice_q1)
data_sp_q4 <- SpatialPoints(d_slice_q4)
# Extract raster value (oxygen)
rasValue_q1 <- raster::extract(r_q1, data_sp_q1)
rasValue_q4 <- raster::extract(r_q4, data_sp_q4)
# Now we want to plot the results of the raster extractions by plotting the cpue
# data points over a raster and saving it for each year.
# Make the SpatialPoints object into a raster again (for pl)
df_q1 <- as.data.frame(data_sp_q1)
df_q4 <- as.data.frame(data_sp_q4)
# Add in the raster value in the df holding the coordinates for the cpue data
d_slice_q1$oxy <- rasValue_q1
d_slice_q4$oxy <- rasValue_q4
# Add in which year
d_slice_q1$year <- i
d_slice_q4$year <- i
# Create a index for the data last where we store all years (because our loop index
# i is not continuous, we can't use it directly)
index_q1 <- as.numeric(as.character(d_slice_q1$year))[1] - 1992
index_q4 <- as.numeric(as.character(d_slice_q4$year))[1] - 1992
# Add each years' data in the list
data_list_q1[[index_q1]] <- d_slice_q1
data_list_q4[[index_q4]] <- d_slice_q4
# Save to check each year is ok! First convert the raster to points for plotting
# (so that we can use ggplot)
map_q1 <- rasterToPoints(r_q1)
map_q4 <- rasterToPoints(r_q4)
# Make the points a dataframe for ggplot
df_rast_q1 <- data.frame(map_q1)
df_rast_q4 <- data.frame(map_q4)
# Rename y-variable and add year
df_rast_q1 <- df_rast_q1 %>% rename("oxy" = "layer") %>% mutate(year = i)
df_rast_q4 <- df_rast_q4 %>% rename("oxy" = "layer") %>% mutate(year = i)
# Add each years' raster data frame in the list
raster_list_q1[[index_q1]] <- df_rast_q1
raster_list_q4[[index_q4]] <- df_rast_q4
# Make appropriate column headings
colnames(df_rast_q1) <- c("Longitude", "Latitude", "oxy")
colnames(df_rast_q4) <- c("Longitude", "Latitude", "oxy")
# Make a map for q1
ggplot(data = df_rast_q1, aes(y = Latitude, x = Longitude)) +
geom_raster(aes(fill = oxy)) +
geom_point(data = d_slice_q1, aes(x = lon, y = lat, fill = oxy),
color = "black", size = 5, shape = 21) +
theme_bw() +
geom_sf(data = world, inherit.aes = F, size = 0.2) +
coord_sf(xlim = c(xmin, xmax),
ylim = c(ymin, ymax)) +
scale_colour_gradientn(colours = rev(terrain.colors(10)),
limits = c(-200, 400)) +
scale_fill_gradientn(colours = rev(terrain.colors(10)),
limits = c(-200, 400)) +
NULL
ggsave(paste("figures/supp/cpue_oxygen_rasters/", i,"q1.png", sep = ""),
width = 6.5, height = 6.5, dpi = 600)
# Make a map for q4
ggplot(data = df_rast_q4, aes(y = Latitude, x = Longitude)) +
geom_raster(aes(fill = oxy)) +
geom_point(data = d_slice_q4, aes(x = lon, y = lat, fill = oxy),
color = "black", size = 5, shape = 21) +
theme_bw() +
geom_sf(data = world, inherit.aes = F, size = 0.2) +
coord_sf(xlim = c(xmin, xmax),
ylim = c(ymin, ymax)) +
scale_colour_gradientn(colours = rev(terrain.colors(10)),
limits = c(-200, 400)) +
scale_fill_gradientn(colours = rev(terrain.colors(10)),
limits = c(-200, 400)) +
NULL
ggsave(paste("figures/supp/cpue_oxygen_rasters/", i,"q4.png", sep = ""),
width = 6.5, height = 6.5, dpi = 600)
}
#> filter: removed 5,043 rows (98%), 101 rows remaining
#> filter: removed 3,392 rows (98%), 61 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,001 rows (97%), 143 rows remaining
#> filter: removed 3,391 rows (98%), 62 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,990 rows (97%), 154 rows remaining
#> filter: removed 3,400 rows (98%), 53 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,009 rows (97%), 135 rows remaining
#> filter: removed 3,392 rows (98%), 61 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,000 rows (97%), 144 rows remaining
#> filter: removed 3,378 rows (98%), 75 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,969 rows (97%), 175 rows remaining
#> filter: removed 3,385 rows (98%), 68 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,973 rows (97%), 171 rows remaining
#> filter: removed 3,359 rows (97%), 94 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,034 rows (98%), 110 rows remaining
#> filter: removed 3,364 rows (97%), 89 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,937 rows (96%), 207 rows remaining
#> filter: removed 3,338 rows (97%), 115 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,002 rows (97%), 142 rows remaining
#> filter: removed 3,336 rows (97%), 117 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,008 rows (97%), 136 rows remaining
#> filter: removed 3,350 rows (97%), 103 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,968 rows (97%), 176 rows remaining
#> filter: removed 3,368 rows (98%), 85 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,959 rows (96%), 185 rows remaining
#> filter: removed 3,332 rows (96%), 121 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,956 rows (96%), 188 rows remaining
#> filter: removed 3,303 rows (96%), 150 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,909 rows (95%), 235 rows remaining
#> filter: removed 3,291 rows (95%), 162 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,923 rows (96%), 221 rows remaining
#> filter: removed 3,277 rows (95%), 176 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,894 rows (95%), 250 rows remaining
#> filter: removed 3,297 rows (95%), 156 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,904 rows (95%), 240 rows remaining
#> filter: removed 3,291 rows (95%), 162 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,901 rows (95%), 243 rows remaining
#> filter: removed 3,273 rows (95%), 180 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,920 rows (96%), 224 rows remaining
#> filter: removed 3,320 rows (96%), 133 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,876 rows (95%), 268 rows remaining
#> filter: removed 3,305 rows (96%), 148 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,936 rows (96%), 208 rows remaining
#> filter: removed 3,277 rows (95%), 176 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,907 rows (95%), 237 rows remaining
#> filter: removed 3,287 rows (95%), 166 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,912 rows (95%), 232 rows remaining
#> filter: removed 3,240 rows (94%), 213 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,899 rows (95%), 245 rows remaining
#> filter: removed 3,228 rows (93%), 225 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 4,888 rows (95%), 256 rows remaining
#> filter: removed 3,243 rows (94%), 210 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 5,026 rows (98%), 118 rows remaining
#> filter: removed 3,361 rows (97%), 92 rows remaining
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> rename: renamed one variable (oxy)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
# Now create a data frame from the list of all annual values
big_dat_oxy_q1 <- dplyr::bind_rows(data_list_q1)
big_dat_oxy_q4 <- dplyr::bind_rows(data_list_q4)
big_dat_oxy <- bind_rows(mutate(big_dat_oxy_q1, quarter = 1),
mutate(big_dat_oxy_q4, quarter = 4))
#> mutate: new variable 'quarter' (double) with one unique value and 0% NA
#> mutate: new variable 'quarter' (double) with one unique value and 0% NA
big_raster_dat_oxy_q1 <- dplyr::bind_rows(raster_list_q1)
big_raster_dat_oxy_q4 <- dplyr::bind_rows(raster_list_q4)
big_raster_dat_oxy <- bind_rows(mutate(big_raster_dat_oxy_q1, quarter = 1),
mutate(big_raster_dat_oxy_q4, quarter = 4))
#> mutate: new variable 'quarter' (double) with one unique value and 0% NA
#> mutate: new variable 'quarter' (double) with one unique value and 0% NA
# Plot data, looks like there's big inter-annual variation but a negative trend over time
big_raster_dat_oxy %>%
group_by(quarter, year) %>%
drop_na(oxy) %>%
summarise(mean_oxy = mean(oxy)) %>%
mutate(year_num = as.numeric(year)) %>%
ggplot(., aes(year_num, mean_oxy)) +
geom_point(size = 2) +
stat_smooth(method = "lm") +
facet_wrap(~ quarter) +
NULL
#> group_by: 2 grouping variables (quarter, year)
#> drop_na (grouped): no rows removed
#> summarise: now 54 rows and 3 columns, one group variable remaining (quarter)
#> mutate (grouped): new variable 'year_num' (double) with 27 unique values and 0% NA
#> `geom_smooth()` using formula 'y ~ x'
big_raster_dat_oxy %>%
group_by(quarter, year) %>%
drop_na(oxy) %>%
mutate(dead = ifelse(oxy < 0, "Y", "N")) %>%
filter(dead == "Y") %>%
mutate(n = n(),
year_num = as.numeric(year)) %>%
ggplot(., aes(year_num, n)) +
geom_point(size = 2) +
stat_smooth(method = "lm") +
facet_wrap(~ quarter) +
NULL
#> group_by: 2 grouping variables (quarter, year)
#> drop_na (grouped): no rows removed
#> mutate (grouped): new variable 'dead' (character) with 2 unique values and 0% NA
#> filter (grouped): removed 877,004 rows (94%), 60,814 rows remaining
#> mutate (grouped): new variable 'n' (integer) with 54 unique values and 0% NA
#> new variable 'year_num' (double) with 27 unique values and 0% NA
#> `geom_smooth()` using formula 'y ~ x'
# Now add in the new oxygen column in the original data:
str(d_sub_oxy_q1)
#> tibble [5,144 × 12] (S3: tbl_df/tbl/data.frame)
#> $ density : num [1:5144] 158.15 10.33 5.26 19.55 812.16 ...
#> $ year : int [1:5144] 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 ...
#> $ lat : num [1:5144] 54.7 54.5 54.5 54.5 54.7 ...
#> $ lon : num [1:5144] 13 14.3 14.2 14 13.1 ...
#> $ quarter : int [1:5144] 1 1 1 1 1 1 1 1 1 1 ...
#> $ haul.id : chr [1:5144] "1993:1:GFR:SOL:H20:21:1" "1993:1:GFR:SOL:H20:22:32" "1993:1:GFR:SOL:H20:23:31" "1993:1:GFR:SOL:H20:24:30" ...
#> $ IDx : chr [1:5144] "1993.1.GFR.06S1.H20.21.1" "1993.1.GFR.06S1.H20.22.32" "1993.1.GFR.06S1.H20.23.31" "1993.1.GFR.06S1.H20.24.30" ...
#> $ ices_rect : chr [1:5144] "38G3" "38G4" "38G4" "37G3" ...
#> $ sub_div : chr [1:5144] "24" "24" "24" "24" ...
#> $ density_fle: num [1:5144] 19.26 13.7 1.99 3.89 34.26 ...
#> $ depth : num [1:5144] 9 7 8 6 13 15 11 15 10 10 ...
#> $ year_f : Factor w/ 27 levels "1993","1994",..: 1 1 1 1 1 1 1 1 1 1 ...
str(d_sub_oxy_q4)
#> tibble [3,453 × 12] (S3: tbl_df/tbl/data.frame)
#> $ density : num [1:3453] 71.71 146.95 864.13 19.48 4.27 ...
#> $ year : int [1:3453] 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 ...
#> $ lat : num [1:3453] 57.5 57.5 54.7 57.1 57.8 ...
#> $ lon : num [1:3453] 17.1 17.6 13.7 18.9 19.5 ...
#> $ quarter : int [1:3453] 4 4 4 4 4 4 4 4 4 4 ...
#> $ haul.id : chr [1:3453] "1993:4:SWE:ARG:FOT:262:31" "1993:4:SWE:ARG:FOT:263:32" "1993:4:GFR:SOL:H20:34:60" "1993:4:SWE:ARG:FOT:256:25" ...
#> $ IDx : chr [1:3453] "1993.4.SWE.77AR.FOT.262.31" "1993.4.SWE.77AR.FOT.263.32" "1993.4.GFR.06S1.H20.34.60" "1993.4.SWE.77AR.FOT.256.25" ...
#> $ ices_rect : chr [1:3453] "43G7" "43G7" "38G3" "43G8" ...
#> $ sub_div : chr [1:3453] "27" "27" "24" "28" ...
#> $ density_fle: num [1:3453] 175.9 13 230.5 25.8 46.5 ...
#> $ depth : num [1:3453] 73 88 20 75 86 10 8 7 32 45 ...
#> $ year_f : Factor w/ 27 levels "1993","1994",..: 1 1 1 1 1 1 1 1 1 1 ...
str(big_dat_oxy)
#> tibble [8,597 × 5] (S3: tbl_df/tbl/data.frame)
#> $ lon : num [1:8597] 13 14.3 14.2 14 13.1 ...
#> $ lat : num [1:8597] 54.7 54.5 54.5 54.5 54.7 ...
#> $ oxy : num [1:8597] 379 397 397 397 377 ...
#> $ year : chr [1:8597] "1993" "1993" "1993" "1993" ...
#> $ quarter: num [1:8597] 1 1 1 1 1 1 1 1 1 1 ...
# Create an ID for matching the oxygen data with the cpue data
dat$id_oxy <- paste(dat$year, dat$quarter, dat$lon, dat$lat, sep = "_")
big_dat_oxy$id_oxy <- paste(big_dat_oxy$year, big_dat_oxy$quarter, big_dat_oxy$lon, big_dat_oxy$lat, sep = "_")
# Which id's are NOT in the cpue data (dat)?
head(dat$id_oxy, 100)
#> [1] "1992_1_13.0333_54.95" "1992_1_13.5_55.0333" "1992_1_13.9_55.1"
#> [4] "1992_1_13.7333_54.8" "1992_1_13.4167_54.8833" "1992_1_14.8667_54.8833"
#> [7] "1992_1_14.5333_54.6333" "1992_1_15.1_55.6333" "1992_1_15.0833_55.25"
#> [10] "1992_1_15.3_55.1" "1992_1_15.7333_55.4333" "1992_1_15.8833_55.5833"
#> [13] "1992_1_15.5833_55.55" "1992_1_16.0667_55.6833" "1992_1_16.25_55.7833"
#> [16] "1992_1_16.4167_55.85" "1992_1_16.9833_56.1" "1992_1_17.65_56.1167"
#> [19] "1992_1_16.65_55.6333" "1992_1_16.5833_55.5833" "1992_1_16.3333_55.3167"
#> [22] "1992_1_16.2167_55.3" "1992_1_16.05_55.25" "1992_1_15.25_54.8167"
#> [25] "1992_1_15.0333_54.8667" "1992_1_18.3_56.1333" "1992_1_18.3667_56.1833"
#> [28] "1992_1_18.5333_56.15" "1992_1_18.5333_56.2" "1992_1_20.9833_57.2667"
#> [31] "1992_1_20.5833_56.6" "1992_1_20.5833_56.6" "1992_1_20.6167_56.6167"
#> [34] "1992_1_13.0833_54.6667" "1992_1_13.1333_54.7167" "1992_1_14.1667_54.5833"
#> [37] "1992_1_14.25_54.6333" "1992_1_13.3167_54.8" "1992_1_13.4667_54.75"
#> [40] "1992_1_13.85_54.5667" "1992_1_13.8667_54.75" "1992_1_13.6667_54.7333"
#> [43] "1992_1_14.0333_54.8667" "1992_1_13.95_54.9333" "1992_1_13.1333_54.8833"
#> [46] "1992_1_13.1167_54.9333" "1992_1_13.2667_54.9833" "1992_1_13.4333_55.0167"
#> [49] "1992_1_13.75_55.1" "1992_1_14.1667_55.15" "1992_1_14.2667_55.1833"
#> [52] "1992_1_14.3333_55.1" "1992_1_14.3_55.0167" "1992_1_13.5667_55.0333"
#> [55] "1992_1_13.8333_55.1" "1992_1_16.9173_57.3635" "1992_1_17.025_57.4033"
#> [58] "1992_1_14.6833_55.58" "1992_1_17.57_57.4783" "1992_1_17.515_56.1467"
#> [61] "1992_1_18.625_56.4767" "1992_1_18.8767_57.1767" "1992_1_18.8683_57.1017"
#> [64] "1992_1_18.885_57.0683" "1992_1_15.37_55.945" "1992_1_18.9_57.0217"
#> [67] "1992_1_17.7967_56.0966" "1992_1_17.7017_55.855" "1992_1_17.1317_55.9267"
#> [70] "1992_1_16.5233_55.6783" "1992_1_14.4433_55.695" "1992_1_15.9483_55.4533"
#> [73] "1992_1_15.8866_55.7983" "1992_1_19.1617_57.3617" "1992_1_19.5333_57.8167"
#> [76] "1992_1_19.53_57.885" "1992_1_19.4633_58.0566" "1992_1_18.1183_57.8083"
#> [79] "1992_1_17.9117_57.3733" "1992_1_17.915_57.1017" "1992_1_17.965_57.045"
#> [82] "1992_1_17.2983_57.14" "1992_1_16.065_55.8767" "1992_1_14.6483_55.4517"
#> [85] "1992_1_14.4457_55.456" "1992_1_13.2_55.2083" "1992_1_13.5917_55.21"
#> [88] "1992_1_13.25_54.97" "1992_1_13.9233_55.0133" "1992_4_13.45_55.0167"
#> [91] "1992_4_13.1_54.9167" "1992_4_13.9667_54.9333" "1992_4_14.35_55.1"
#> [94] "1992_4_14.1667_55.1333" "1992_4_13.9_54.5" "1992_4_14.2_54.5"
#> [97] "1992_4_14.2833_55.1833" "1992_4_13.8_54.5167" "1992_4_14.3667_54.5167"
#> [100] "1992_4_13.8833_54.5667"
head(big_dat_oxy$id_oxy, 100)
#> [1] "1993_1_13_54.6833" "1993_1_14.2667_54.5167" "1993_1_14.15_54.5167"
#> [4] "1993_1_13.9833_54.4833" "1993_1_13.0833_54.7333" "1993_1_13.1833_54.7"
#> [7] "1993_1_13.8_54.55" "1993_1_14.1167_54.7" "1993_1_14.0833_54.5833"
#> [10] "1993_1_13.8667_54.5833" "1993_1_14.15_54.6333" "1993_1_13.3667_54.7333"
#> [13] "1993_1_13.5167_54.7333" "1993_1_13.6333_54.6833" "1993_1_13.7333_54.6667"
#> [16] "1993_1_13.85_54.7" "1993_1_13.6667_54.7667" "1993_1_14.0167_54.85"
#> [19] "1993_1_13.8833_54.9667" "1993_1_13.6167_54.9167" "1993_1_13.2167_54.8667"
#> [22] "1993_1_13.1_54.9333" "1993_1_13.3167_54.9833" "1993_1_13.4333_55.0333"
#> [25] "1993_1_13.75_55.0667" "1993_1_14.1667_55.1333" "1993_1_14.2667_55.1667"
#> [28] "1993_1_14.2833_55.0667" "1993_1_14.2333_55" "1993_1_13.6167_55.05"
#> [31] "1993_1_13.8167_55.0833" "1993_1_16.6_54.8667" "1993_1_15.1167_54.3"
#> [34] "1993_1_16.5167_54.8333" "1993_1_15.0167_54.4333" "1993_1_16.6333_54.85"
#> [37] "1993_1_15.7667_54.3667" "1993_1_16.0167_54.4333" "1993_1_15.3333_55.9333"
#> [40] "1993_1_15.7167_54.4333" "1993_1_16.2167_54.9167" "1993_1_16.3_55.8333"
#> [43] "1993_1_15.95_54.7833" "1993_1_17.6167_56.0833" "1993_1_15.6_55.9167"
#> [46] "1993_1_15.5833_54.6167" "1993_1_16.2333_55.7833" "1993_1_17.75_56.1333"
#> [49] "1993_1_15.1167_55.6833" "1993_1_16.4333_55.45" "1993_1_14.8667_55.6167"
#> [52] "1993_1_15.6_54.7667" "1993_1_16.35_55.3667" "1993_1_15.8833_55.6"
#> [55] "1993_1_15.7_55.6" "1993_1_17.35_55.2667" "1993_1_16.2_55.3"
#> [58] "1993_1_15.1667_55.4333" "1993_1_17.55_55.25" "1993_1_16.05_55.1333"
#> [61] "1993_1_14.5143_55.6712" "1993_1_16.611_55.6187" "1993_1_16.8935_55.785"
#> [64] "1993_1_14.7333_55.455" "1993_1_14.5483_55.465" "1993_1_13.9913_54.9983"
#> [67] "1993_1_13.6493_55.213" "1993_1_13.32_54.935" "1993_1_13.2767_55.21"
#> [70] "1993_1_15.4393_55.8218" "1993_1_15.46_55.9933" "1993_1_19.5368_57.8885"
#> [73] "1993_1_16.1217_55.795" "1993_1_16.085_55.8733" "1993_1_17.0855_55.8667"
#> [76] "1993_1_17.1323_55.9248" "1993_1_17.7367_55.8015" "1993_1_17.7188_56.0352"
#> [79] "1993_1_16.9745_56.445" "1993_1_16.8225_56.5178" "1993_1_17.94_57.004"
#> [82] "1993_1_14.7172_55.5687" "1993_1_17.9145_57.066" "1993_1_16.9133_57.3685"
#> [85] "1993_1_17.0157_57.5172" "1993_1_17.5322_57.4502" "1993_1_18.123_57.821"
#> [88] "1993_1_18.3128_57.7555" "1993_1_16.0507_55.3282" "1993_1_15.3205_55.412"
#> [91] "1993_1_19.5493_57.8677" "1993_1_19.0568_57.5685" "1993_1_19.1942_57.3825"
#> [94] "1993_1_18.8761_57.1808" "1993_1_18.8363_57.085" "1993_1_18.9005_57.089"
#> [97] "1993_1_18.4828_56.2562" "1993_1_18.3732_55.5878" "1993_1_16.9951_55.2882"
#> [100] "1993_1_17.5_55"
tail(dat$id_oxy, 100)
#> [1] "2018_4_20.37_57.0317" "2018_4_20.3383_56.6" "2018_4_20.1317_56.4817"
#> [4] "2018_4_20.0833_56.4333" "2018_4_19.7067_56.38" "2018_4_19.525_56.3"
#> [7] "2018_4_19.4933_58.035" "2018_4_19.5305_57.8297" "2018_4_18.1183_57.79"
#> [10] "2018_4_16.0635_55.1584" "2018_4_16.053_55.1374" "2018_4_15.7322_55.0559"
#> [13] "2018_4_17.7017_55.78" "2018_4_20.5933_57.34" "2018_4_15.4397_55.7654"
#> [16] "2018_4_14.7118_55.6254" "2018_4_14.8696_55.623" "2018_4_15.255_55.5437"
#> [19] "2018_4_16.1757_55.5421" "2018_4_15.5875_55.5354" "2018_4_14.9434_55.5179"
#> [22] "2018_4_15.5546_55.466" "2018_4_15.9157_55.4343" "2018_4_15.2662_55.3745"
#> [25] "2018_4_16.0234_55.3034" "2018_4_15.9613_55.2382" "2018_4_19.4517_56.2"
#> [28] "2018_4_20.2267_55.7667" "2018_4_20.06_55.735" "2018_4_19.9767_55.6683"
#> [31] "2018_4_20.275_55.6583" "2018_4_20.1567_55.6433" "2018_4_18.9933_55.5083"
#> [34] "2019_1_18.5467_56.3017" "2019_1_19.4592_56.199" "2019_1_19.5188_56.28"
#> [37] "2019_1_19.6268_56.3762" "2019_1_19.8065_56.4432" "2019_1_17.9563_57.0228"
#> [40] "2019_1_17.9102_57.074" "2019_1_17.2842_57.0972" "2019_1_17.4182_57.3255"
#> [43] "2019_1_19.1467_57.3458" "2019_1_18.3733_55.605" "2019_1_19.083_57.3555"
#> [46] "2019_1_17.5442_57.4563" "2019_1_19.2515_57.4993" "2019_1_18.5867_56.385"
#> [49] "2019_1_17.0822_57.6312" "2019_1_19.4818_57.7923" "2019_1_15.73_54.3783"
#> [52] "2019_4_19.1013_57.2805" "2019_4_17.8862_57.3405" "2019_4_16.997_57.4457"
#> [55] "2019_4_17.0787_57.6348" "2019_4_18.3157_57.755" "2019_4_18.1202_57.7905"
#> [58] "2019_4_19.5262_57.8475" "2019_4_19.5033_56.2167" "2019_4_19.4908_56.2172"
#> [61] "2019_4_18.6763_56.3202" "2019_4_18.6765_56.4617" "2020_1_18.8967_54.55"
#> [64] "2020_1_18.7983_55.3583" "2020_1_17.0433_55.3833" "2020_1_19.049_57.1968"
#> [67] "2020_1_18.828_57.1662" "2020_1_18.9622_57.1165" "2020_1_19.439_58.075"
#> [70] "2020_1_19.4817_57.7677" "2020_1_17.7363_57.4597" "2020_1_17.9093_57.0747"
#> [73] "2020_1_18.8312_57.0655" "2020_1_18.8742_57.0632" "2020_1_19.11_57.321"
#> [76] "2020_1_19.2567_54.3883" "2020_4_21.4283_57.4983" "2020_4_20.5433_57.0467"
#> [79] "2020_4_20.08_56.3833" "2020_4_18.015_55.69" "2020_4_16.9165_57.3647"
#> [82] "2020_4_19.2267_57.3361" "2020_4_19.1085_57.319" "2020_4_17.4146_57.2805"
#> [85] "2020_4_19.0668_57.2496" "2020_4_18.9076_57.089" "2020_4_19.4891_58.0354"
#> [88] "2020_4_19.5044_57.876" "2020_4_18.1196_57.7804" "2020_4_19.4807_57.7685"
#> [91] "2020_4_19.3769_57.6885" "2020_4_17.0977_57.6175" "2020_4_17.5616_57.4828"
#> [94] "2020_4_17.0912_57.4622" "2020_4_17.9167_57.0532" "2020_4_17.9509_56.9956"
#> [97] "2020_4_17.184_56.9584" "2020_4_16.9939_56.7256" "2020_4_16.85_56.5655"
#> [100] "2020_4_19.439_58.0746"
tail(big_dat_oxy$id_oxy, 100)
#> [1] "2018_4_15.9613_55.2382" "2018_4_19.4517_56.2" "2018_4_20.2267_55.7667"
#> [4] "2018_4_20.06_55.735" "2018_4_19.9767_55.6683" "2018_4_20.275_55.6583"
#> [7] "2018_4_20.1567_55.6433" "2018_4_18.9933_55.5083" "2019_4_17.3133_55.3233"
#> [10] "2019_4_14.529_55.4627" "2019_4_18.6817_54.785" "2019_4_18.7083_54.7833"
#> [13] "2019_4_18.75_54.7317" "2019_4_18.9583_54.565" "2019_4_14.6418_55.4718"
#> [16] "2019_4_18.535_54.8133" "2019_4_17.2767_55.3117" "2019_4_14.3668_55.696"
#> [19] "2019_4_15.955_54.75" "2019_4_16.915_57.365" "2019_4_14.3798_55.7077"
#> [22] "2019_4_17.3167_55.2383" "2019_4_14.4607_55.6847" "2019_4_14.51_55.6878"
#> [25] "2019_4_14.374_55.7028" "2019_4_17.9512_56.992" "2019_4_19.1683_54.6"
#> [28] "2019_4_17.9208_57.0495" "2019_4_19.5073_57.8783" "2019_4_19.31_54.6267"
#> [31] "2019_4_18.8628_57.1762" "2019_4_17.1777_56.944" "2019_4_19.2217_54.6333"
#> [34] "2019_4_19.3283_54.45" "2019_4_19.3033_54.4283" "2019_4_19.305_54.4167"
#> [37] "2019_4_19.2983_54.4" "2019_4_16.885_54.7417" "2019_4_16.8333_54.7483"
#> [40] "2019_4_16.6767_54.7017" "2019_4_16.4183_54.6567" "2019_4_16.045_54.83"
#> [43] "2019_4_16.0683_54.6317" "2019_4_15.8267_54.4667" "2019_4_18.961_57.2812"
#> [46] "2019_4_16.035_54.4083" "2019_4_16.0567_54.4383" "2019_4_15.7667_54.38"
#> [49] "2019_4_15.6433_54.3817" "2019_4_16.21_55.045" "2019_4_17.4917_54.8517"
#> [52] "2019_4_17.4233_54.955" "2019_4_18.4888_56.3935" "2019_4_17.4533_54.995"
#> [55] "2019_4_16.705_54.8783" "2019_4_16.8033_55.42" "2019_4_17.2667_55.4567"
#> [58] "2019_4_17.3933_55.385" "2019_4_18.1817_54.9017" "2019_4_18.535_54.985"
#> [61] "2019_4_18.6372_55.9193" "2019_4_18.58_54.8517" "2019_4_18.4312_56.2255"
#> [64] "2019_4_18.5417_54.9817" "2019_4_18.6_54.9133" "2019_4_18.4437_56.3492"
#> [67] "2019_4_18.635_54.8883" "2019_4_18.655_54.895" "2019_4_19.1783_54.4317"
#> [70] "2019_4_19.0633_54.4433" "2019_4_19.0617_54.4367" "2019_4_16.9977_56.6928"
#> [73] "2019_4_19.0417_54.4017" "2019_4_19.0167_54.405" "2019_4_15.5732_55.8533"
#> [76] "2019_4_18.99_54.4017" "2019_4_19.04_54.94" "2019_4_15.2227_55.7868"
#> [79] "2019_4_18.8167_54.9733" "2019_4_18.8_54.965" "2019_4_18.645_55.1767"
#> [82] "2019_4_18.33_55.465" "2019_4_14.4635_55.6833" "2019_4_18.325_55.4583"
#> [85] "2019_4_18.7733_55.8883" "2019_4_18.0533_55.6317" "2019_4_17.5967_55.6167"
#> [88] "2019_4_17.5533_55.3933" "2019_4_17.76_55.395" "2019_4_19.1013_57.2805"
#> [91] "2019_4_17.8862_57.3405" "2019_4_16.997_57.4457" "2019_4_17.0787_57.6348"
#> [94] "2019_4_18.3157_57.755" "2019_4_18.1202_57.7905" "2019_4_19.5262_57.8475"
#> [97] "2019_4_19.5033_56.2167" "2019_4_19.4908_56.2172" "2019_4_18.6763_56.3202"
#> [100] "2019_4_18.6765_56.4617"
#dat %>% group_by(year) %>% summarise(n = n()) %>% as.data.frame()
ids <- dat$id_oxy[!dat$id_oxy %in% c(big_dat_oxy$id_oxy)]
dat %>% filter(id_oxy %in% ids)
#> filter: removed 8,597 rows (96%), 342 rows remaining
#> # A tibble: 342 × 12
#> density year lat lon quarter haul.id IDx ices_rect sub_div density_fle
#> <dbl> <int> <dbl> <dbl> <int> <chr> <chr> <chr> <chr> <dbl>
#> 1 25.0 1992 55.0 13.0 1 1992:1… 1992… 38G3 24 13.1
#> 2 96.4 1992 55.0 13.5 1 1992:1… 1992… 39G3 24 117.
#> 3 141. 1992 55.1 13.9 1 1992:1… 1992… 39G3 24 267.
#> 4 102. 1992 54.8 13.7 1 1992:1… 1992… 38G3 24 57.2
#> 5 133. 1992 54.9 13.4 1 1992:1… 1992… 38G3 24 80.6
#> 6 46.4 1992 54.9 14.9 1 1992:1… 1992… 38G4 24 21.3
#> 7 45.4 1992 54.6 14.5 1 1992:1… 1992… 38G4 24 17.8
#> 8 733. 1992 55.6 15.1 1 1992:1… 1992… 40G5 25 790.
#> 9 133. 1992 55.2 15.1 1 1992:1… 1992… 39G5 25 141.
#> 10 200. 1992 55.1 15.3 1 1992:1… 1992… 39G5 25 286.
#> # … with 332 more rows, and 2 more variables: depth <dbl>, id_oxy <chr>
# Select only the columns we want to merge
big_dat_sub_oxy <- big_dat_oxy %>% dplyr::select(id_oxy, oxy)
# Remove duplicate ID (one oxy value per id)
big_dat_sub_oxy %>% group_by(id_oxy) %>% mutate(n = n()) %>% arrange(desc(n))
#> group_by: one grouping variable (id_oxy)
#> mutate (grouped): new variable 'n' (integer) with 4 unique values and 0% NA
#> # A tibble: 8,597 × 3
#> # Groups: id_oxy [8,576]
#> id_oxy oxy n
#> <chr> <dbl> <int>
#> 1 1999_1_15.3667_54.5667 315. 4
#> 2 1999_1_15.3667_54.5667 315. 4
#> 3 1999_1_15.3667_54.5667 315. 4
#> 4 1999_1_15.3667_54.5667 315. 4
#> 5 1999_4_15.2833_55.8 164. 3
#> 6 1999_4_15.2833_55.8 164. 3
#> 7 1999_4_15.2833_55.8 164. 3
#> 8 1995_1_18.7833_54.6833 387. 2
#> 9 1995_1_18.7833_54.6833 387. 2
#> 10 1995_1_18.65_54.8667 381. 2
#> # … with 8,587 more rows
big_dat_sub_oxy2 <- big_dat_sub_oxy %>% distinct(id_oxy, .keep_all = TRUE)
#> distinct: removed 21 rows (<1%), 8,576 rows remaining
# Join the data with raster-derived oxygen with the full cpue data
dat <- left_join(dat, big_dat_sub_oxy2, by = "id_oxy")
#> left_join: added one column (oxy)
#> > rows only in x 342
#> > rows only in y ( 0)
#> > matched rows 8,597
#> > =======
#> > rows total 8,939
# Now the unit of oxygen is mmol/m3. I want it to be ml/L. The original model is in unit ml/L
# and it's been converted by the data host. Since it was converted without accounting for
# pressure or temperature, I can simply use the following conversion factor:
# 1 ml/l = 103/22.391 = 44.661 μmol/l -> 1 ml/l = 0.044661 mmol/l = 44.661 mmol/m^3 -> 0.0223909 ml/l = 1mmol/m^3
# https://ocean.ices.dk/tools/unitconversion.aspx
dat$oxy <- dat$oxy * 0.0223909
# Drop NA oxygen
dat <- dat %>% drop_na(oxy)
#> drop_na: removed 369 rows (4%), 8,570 rows remaining
sort(unique(dat$year))
#> [1] 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
#> [16] 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019Temperature
# Open the netCDF file
ncin <- nc_open("data/NEMO_Nordic_SCOBI/dataset-reanalysis-nemo-monthlymeans_1608127623694.nc")
print(ncin)
#> File data/NEMO_Nordic_SCOBI/dataset-reanalysis-nemo-monthlymeans_1608127623694.nc (NC_FORMAT_CLASSIC):
#>
#> 1 variables (excluding dimension variables):
#> float bottomT[longitude,latitude,time]
#> standard_name: sea_water_potential_temperature_at_sea_floor
#> units: degrees_C
#> long_name: Sea floor potential temperature
#> missing_value: NaN
#> _FillValue: NaN
#> _ChunkSizes: 1
#> _ChunkSizes: 523
#> _ChunkSizes: 383
#>
#> 3 dimensions:
#> time Size:324
#> axis: T
#> long_name: Validity time
#> standard_name: time
#> units: days since 1950-01-01 00:00:00
#> calendar: gregorian
#> _ChunkSizes: 512
#> _CoordinateAxisType: Time
#> valid_min: 15721.5
#> valid_max: 25551.5
#> latitude Size:523
#> axis: Y
#> standard_name: latitude
#> long_name: latitude
#> units: degrees_north
#> _CoordinateAxisType: Lat
#> valid_min: 48.49169921875
#> valid_max: 65.8914184570312
#> longitude Size:383
#> standard_name: longitude
#> long_name: longitude
#> units: degrees_east
#> axis: X
#> _CoordinateAxisType: Lon
#> valid_min: 9.01375484466553
#> valid_max: 30.2357654571533
#>
#> 24 global attributes:
#> references: http://www.smhi.se
#> institution: Swedish Meterological and Hydrological Institute
#> history: See source and creation_date attributees
#> Conventions: CF-1.5
#> contact: servicedesk_cmems@mercator-ocean.eu
#> comment: Provided by SMHI as a Copernicus Marine Environment Monitoring Service production unit
#> bullentin_type: reanalysis
#> cmems_product_id: BALTICSEA_REANALYSIS_PHY_003_011
#> title: CMEMS V4 Reanalysis: NEMO model 3D fields (monthly means)
#> FROM_ORIGINAL_FILE__easternmost_longitude: 30.2357654571533
#> FROM_ORIGINAL_FILE__northernmost_latitude: 65.8914184570312
#> FROM_ORIGINAL_FILE__westernmost_longitude: 9.01375484466553
#> FROM_ORIGINAL_FILE__southernmost_latitude: 48.49169921875
#> shallowest_depth: 1.50136542320251
#> deepest_depth: 711.059204101562
#> source: SMHI reanalysis run NORDIC-NS2_1d_20191201_20191202
#> file_quality_index: 1
#> creation_date: 2020-11-16 UTC
#> bullentin_date: 20191201
#> start_date: 2019-12-01 UTC
#> stop_date: 2019-12-01 UTC
#> start_time: 00:00 UTC
#> stop_time: 00:00 UTC
#> _CoordSysBuilder: ucar.nc2.dataset.conv.CF1Convention
# Get longitude and latitude
lon <- ncvar_get(ncin,"longitude")
nlon <- dim(lon)
head(lon)
#> [1] 9.013755 9.069310 9.124865 9.180420 9.235975 9.291530
lat <- ncvar_get(ncin,"latitude")
nlat <- dim(lat)
head(lat)
#> [1] 48.49170 48.52503 48.55836 48.59170 48.62503 48.65836
# Get time
time <- ncvar_get(ncin,"time")
time
#> [1] 15721.5 15751.0 15780.5 15811.0 15841.5 15872.0 15902.5 15933.5 15964.0
#> [10] 15994.5 16025.0 16055.5 16086.5 16116.0 16145.5 16176.0 16206.5 16237.0
#> [19] 16267.5 16298.5 16329.0 16359.5 16390.0 16420.5 16451.5 16481.0 16510.5
#> [28] 16541.0 16571.5 16602.0 16632.5 16663.5 16694.0 16724.5 16755.0 16785.5
#> [37] 16816.5 16846.5 16876.5 16907.0 16937.5 16968.0 16998.5 17029.5 17060.0
#> [46] 17090.5 17121.0 17151.5 17182.5 17212.0 17241.5 17272.0 17302.5 17333.0
#> [55] 17363.5 17394.5 17425.0 17455.5 17486.0 17516.5 17547.5 17577.0 17606.5
#> [64] 17637.0 17667.5 17698.0 17728.5 17759.5 17790.0 17820.5 17851.0 17881.5
#> [73] 17912.5 17942.0 17971.5 18002.0 18032.5 18063.0 18093.5 18124.5 18155.0
#> [82] 18185.5 18216.0 18246.5 18277.5 18307.5 18337.5 18368.0 18398.5 18429.0
#> [91] 18459.5 18490.5 18521.0 18551.5 18582.0 18612.5 18643.5 18673.0 18702.5
#> [100] 18733.0 18763.5 18794.0 18824.5 18855.5 18886.0 18916.5 18947.0 18977.5
#> [109] 19008.5 19038.0 19067.5 19098.0 19128.5 19159.0 19189.5 19220.5 19251.0
#> [118] 19281.5 19312.0 19342.5 19373.5 19403.0 19432.5 19463.0 19493.5 19524.0
#> [127] 19554.5 19585.5 19616.0 19646.5 19677.0 19707.5 19738.5 19768.5 19798.5
#> [136] 19829.0 19859.5 19890.0 19920.5 19951.5 19982.0 20012.5 20043.0 20073.5
#> [145] 20104.5 20134.0 20163.5 20194.0 20224.5 20255.0 20285.5 20316.5 20347.0
#> [154] 20377.5 20408.0 20438.5 20469.5 20499.0 20528.5 20559.0 20589.5 20620.0
#> [163] 20650.5 20681.5 20712.0 20742.5 20773.0 20803.5 20834.5 20864.0 20893.5
#> [172] 20924.0 20954.5 20985.0 21015.5 21046.5 21077.0 21107.5 21138.0 21168.5
#> [181] 21199.5 21229.5 21259.5 21290.0 21320.5 21351.0 21381.5 21412.5 21443.0
#> [190] 21473.5 21504.0 21534.5 21565.5 21595.0 21624.5 21655.0 21685.5 21716.0
#> [199] 21746.5 21777.5 21808.0 21838.5 21869.0 21899.5 21930.5 21960.0 21989.5
#> [208] 22020.0 22050.5 22081.0 22111.5 22142.5 22173.0 22203.5 22234.0 22264.5
#> [217] 22295.5 22325.0 22354.5 22385.0 22415.5 22446.0 22476.5 22507.5 22538.0
#> [226] 22568.5 22599.0 22629.5 22660.5 22690.5 22720.5 22751.0 22781.5 22812.0
#> [235] 22842.5 22873.5 22904.0 22934.5 22965.0 22995.5 23026.5 23056.0 23085.5
#> [244] 23116.0 23146.5 23177.0 23207.5 23238.5 23269.0 23299.5 23330.0 23360.5
#> [253] 23391.5 23421.0 23450.5 23481.0 23511.5 23542.0 23572.5 23603.5 23634.0
#> [262] 23664.5 23695.0 23725.5 23756.5 23786.0 23815.5 23846.0 23876.5 23907.0
#> [271] 23937.5 23968.5 23999.0 24029.5 24060.0 24090.5 24121.5 24151.5 24181.5
#> [280] 24212.0 24242.5 24273.0 24303.5 24334.5 24365.0 24395.5 24426.0 24456.5
#> [289] 24487.5 24517.0 24546.5 24577.0 24607.5 24638.0 24668.5 24699.5 24730.0
#> [298] 24760.5 24791.0 24821.5 24852.5 24882.0 24911.5 24942.0 24972.5 25003.0
#> [307] 25033.5 25064.5 25095.0 25125.5 25156.0 25186.5 25217.5 25247.0 25276.5
#> [316] 25307.0 25337.5 25368.0 25398.5 25429.5 25460.0 25490.5 25521.0 25551.5
tunits <- ncatt_get(ncin,"time","units")
nt <- dim(time)
nt
#> [1] 324
tunits
#> $hasatt
#> [1] TRUE
#>
#> $value
#> [1] "days since 1950-01-01 00:00:00"
# Get temperature
dname <- "bottomT"
temp_array <- ncvar_get(ncin,dname)
dlname <- ncatt_get(ncin,dname,"long_name")
dunits <- ncatt_get(ncin,dname,"units")
fillvalue <- ncatt_get(ncin,dname,"_FillValue")
dim(temp_array)
#> [1] 383 523 324
# Get global attributes
title <- ncatt_get(ncin,0,"title")
institution <- ncatt_get(ncin,0,"institution")
datasource <- ncatt_get(ncin,0,"source")
references <- ncatt_get(ncin,0,"references")
history <- ncatt_get(ncin,0,"history")
Conventions <- ncatt_get(ncin,0,"Conventions")
# Convert time: split the time units string into fields
tustr <- strsplit(tunits$value, " ")
tdstr <- strsplit(unlist(tustr)[3], "-")
tmonth <- as.integer(unlist(tdstr)[2])
tday <- as.integer(unlist(tdstr)[3])
tyear <- as.integer(unlist(tdstr)[1])
# Here I deviate from the guide a little bit. Save this info:
dates <- chron(time, origin = c(tmonth, tday, tyear))
# Crop the date variable
months <- as.numeric(substr(dates, 2, 3))
years <- as.numeric(substr(dates, 8, 9))
years <- ifelse(years > 90, 1900 + years, 2000 + years)
# Replace netCDF fill values with NA's
temp_array[temp_array == fillvalue$value] <- NA
# We only use Quarter 4 in this analysis, so now we want to loop through each time step,
# and if it is a good month save it as a raster.
# First get the index of months that correspond to Q4
months
#> [1] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1
#> [26] 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2
#> [51] 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
#> [76] 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
#> [101] 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5
#> [126] 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6
#> [151] 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7
#> [176] 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8
#> [201] 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9
#> [226] 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10
#> [251] 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11
#> [276] 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
#> [301] 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12
index_keep <- which(months > 9)
# Quarter 4 by keeping months in index_keep
temp_q4 <- temp_array[, , index_keep]
months_keep <- months[index_keep]
years_keep <- years[index_keep]
# Now we have an array with only Q4 data...
# We need to now calculate the average within a year.
# Get a sequence that takes every third value between 1: number of months (length)
loop_seq <- seq(1, dim(temp_q4)[3], by = 3)
# Create objects that will hold data
dlist <- list()
temp_10 <- c()
temp_11 <- c()
temp_12 <- c()
temp_ave <- c()
# Loop through the vector sequence with every third value, then take the average of
# three consecutive months (i.e. q4)
for(i in loop_seq) {
temp_10 <- temp_q4[, , (i)]
temp_11 <- temp_q4[, , (i + 1)]
temp_12 <- temp_q4[, , (i + 2)]
temp_ave <- (temp_10 + temp_11 + temp_12) / 3
list_pos <- ((i/3) - (1/3)) + 1 # to get index 1:n(years)
dlist[[list_pos]] <- temp_ave
}
# Now name the lists with the year:
names(dlist) <- unique(years_keep)
# Now I need to make a loop where I extract the raster value for each year...
# The cpue data is called dat so far in this script
# Filter years in the cpue data frame to only have the years I have temperature for
d_sub_temp <- dat %>% filter(year %in% names(dlist)) %>% droplevels()
#> filter: no rows removed
# Create data holding object
data_list <- list()
# ... And for the temperature raster
raster_list <- list()
# Create factor year for indexing the list in the loop
d_sub_temp$year_f <- as.factor(d_sub_temp$year)
# Loop through each year and extract raster values for the cpue data points
for(i in unique(d_sub_temp$year_f)) {
# Subset a year
temp_slice <- dlist[[i]]
# Create raster for that year (i)
r <- raster(t(temp_slice), xmn = min(lon), xmx = max(lon), ymn = min(lat), ymx = max(lat),
crs = CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs+ towgs84=0,0,0"))
# Flip...
r <- flip(r, direction = 'y')
#plot(r, main = i)
# Filter the same year (i) in the cpue data and select only coordinates
d_slice <- d_sub_temp %>% filter(year_f == i) %>% dplyr::select(lon, lat)
# Make into a SpatialPoints object
data_sp <- SpatialPoints(d_slice)
# Extract raster value (temperature)
rasValue <- raster::extract(r, data_sp)
# Now we want to plot the results of the raster extractions by plotting the cpue
# data points over a raster and saving it for each year.
# Make the SpatialPoints object into a raster again (for pl)
df <- as.data.frame(data_sp)
# Add in the raster value in the df holding the coordinates for the cpue data
d_slice$temp <- rasValue
# Add in which year
d_slice$year <- i
# Create a index for the data last where we store all years (because our loop index
# i is not continuous, we can't use it directly)
index <- as.numeric(d_slice$year)[1] - 1992
# Add each years' data in the list
data_list[[index]] <- d_slice
# Save to check each year is ok! First convert the raster to points for plotting
# (so that we can use ggplot)
map.p <- rasterToPoints(r)
# Make the points a dataframe for ggplot
df_rast <- data.frame(map.p)
# Rename y-variable and add year
df_rast <- df_rast %>% rename("temp" = "layer") %>% mutate(year = i)
# Add each years' raster data frame in the list
raster_list[[index]] <- df_rast
# Make appropriate column headings
colnames(df_rast) <- c("Longitude", "Latitude", "temp")
# Now make the map
ggplot(data = df_rast, aes(y = Latitude, x = Longitude)) +
geom_raster(aes(fill = temp)) +
geom_point(data = d_slice, aes(x = lon, y = lat, fill = temp),
color = "black", size = 5, shape = 21) +
theme_bw() +
geom_sf(data = world, inherit.aes = F, size = 0.2) +
coord_sf(xlim = c(min(dat$lon), max(dat$lon)),
ylim = c(min(dat$lat), max(dat$lat))) +
scale_colour_gradientn(colours = rev(terrain.colors(10)),
limits = c(2, 17)) +
scale_fill_gradientn(colours = rev(terrain.colors(10)),
limits = c(2, 17)) +
NULL
ggsave(paste("figures/supp/cpue_temp_rasters/", i,".png", sep = ""),
width = 6.5, height = 6.5, dpi = 600)
}
#> filter: removed 8,409 rows (98%), 161 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,366 rows (98%), 204 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,365 rows (98%), 205 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,374 rows (98%), 196 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,351 rows (97%), 219 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,327 rows (97%), 243 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,309 rows (97%), 261 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,371 rows (98%), 199 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,251 rows (96%), 319 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,311 rows (97%), 259 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,331 rows (97%), 239 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,309 rows (97%), 261 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,265 rows (96%), 305 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,233 rows (96%), 337 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,175 rows (95%), 395 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,175 rows (95%), 395 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,166 rows (95%), 404 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,169 rows (95%), 401 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,148 rows (95%), 422 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,214 rows (96%), 356 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,154 rows (95%), 416 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,186 rows (96%), 384 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,167 rows (95%), 403 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,127 rows (95%), 443 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,101 rows (95%), 469 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,105 rows (95%), 465 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
#> filter: removed 8,361 rows (98%), 209 rows remaining
#> rename: renamed one variable (temp)
#> mutate: new variable 'year' (character) with one unique value and 0% NA
# Now create a data frame from the list of all annual values
big_dat_temp <- dplyr::bind_rows(data_list)
big_raster_dat_temp <- dplyr::bind_rows(raster_list)
big_dat_temp %>% drop_na(temp) %>% summarise(max = max(temp))
#> drop_na: no rows removed
#> summarise: now one row and one column, ungrouped
#> # A tibble: 1 × 1
#> max
#> <dbl>
#> 1 14.5
big_dat_temp %>% drop_na(temp) %>% summarise(min = min(temp))
#> drop_na: no rows removed
#> summarise: now one row and one column, ungrouped
#> # A tibble: 1 × 1
#> min
#> <dbl>
#> 1 2.82
# Plot data, looks like there's big inter-annual variation but a positive trend
big_raster_dat_temp %>%
group_by(year) %>%
drop_na(temp) %>%
summarise(mean_temp = mean(temp)) %>%
mutate(year_num = as.numeric(year)) %>%
ggplot(., aes(year_num, mean_temp)) +
geom_point(size = 2) +
stat_smooth(method = "lm") +
NULL
#> group_by: one grouping variable (year)
#> drop_na (grouped): no rows removed
#> summarise: now 27 rows and 2 columns, ungrouped
#> mutate: new variable 'year_num' (double) with 27 unique values and 0% NA
#> `geom_smooth()` using formula 'y ~ x'
# Now add in the new temperature column in the original data:
str(d_sub_temp)
#> tibble [8,570 × 14] (S3: tbl_df/tbl/data.frame)
#> $ density : num [1:8570] 158.15 10.33 5.26 19.55 812.16 ...
#> $ year : int [1:8570] 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 ...
#> $ lat : num [1:8570] 54.7 54.5 54.5 54.5 54.7 ...
#> $ lon : num [1:8570] 13 14.3 14.2 14 13.1 ...
#> $ quarter : int [1:8570] 1 1 1 1 1 1 1 1 1 1 ...
#> $ haul.id : chr [1:8570] "1993:1:GFR:SOL:H20:21:1" "1993:1:GFR:SOL:H20:22:32" "1993:1:GFR:SOL:H20:23:31" "1993:1:GFR:SOL:H20:24:30" ...
#> $ IDx : chr [1:8570] "1993.1.GFR.06S1.H20.21.1" "1993.1.GFR.06S1.H20.22.32" "1993.1.GFR.06S1.H20.23.31" "1993.1.GFR.06S1.H20.24.30" ...
#> $ ices_rect : chr [1:8570] "38G3" "38G4" "38G4" "37G3" ...
#> $ sub_div : chr [1:8570] "24" "24" "24" "24" ...
#> $ density_fle: num [1:8570] 19.26 13.7 1.99 3.89 34.26 ...
#> $ depth : num [1:8570] 9 7 8 6 13 15 11 15 10 10 ...
#> $ id_oxy : chr [1:8570] "1993_1_13_54.6833" "1993_1_14.2667_54.5167" "1993_1_14.15_54.5167" "1993_1_13.9833_54.4833" ...
#> $ oxy : num [1:8570] 8.49 8.89 8.9 8.89 8.45 ...
#> $ year_f : Factor w/ 27 levels "1993","1994",..: 1 1 1 1 1 1 1 1 1 1 ...
str(big_dat_temp)
#> tibble [8,570 × 4] (S3: tbl_df/tbl/data.frame)
#> $ lon : num [1:8570] 13 14.3 14.2 14 13.1 ...
#> $ lat : num [1:8570] 54.7 54.5 54.5 54.5 54.7 ...
#> $ temp: num [1:8570] 8.14 7.45 7.42 7.37 8.1 ...
#> $ year: chr [1:8570] "1993" "1993" "1993" "1993" ...
# Create an ID for matching the temperature data with the cpue data
dat$id_temp <- paste(dat$year, dat$lon, dat$lat, sep = "_")
big_dat_temp$id_temp <- paste(big_dat_temp$year, big_dat_temp$lon, big_dat_temp$lat, sep = "_")
# Which id's are not in the cpue data (dat)? (It's because I don't have those years, not about the location)
ids <- dat$id_temp[!dat$id_temp %in% c(big_dat_temp$id_temp)]
unique(ids)
#> character(0)
# Select only the columns we want to merge
big_dat_sub_temp <- big_dat_temp %>% dplyr::select(id_temp, temp)
# Remove duplicate ID (one temp value per id)
big_dat_sub_temp2 <- big_dat_sub_temp %>% distinct(id_temp, .keep_all = TRUE)
#> distinct: removed 87 rows (1%), 8,483 rows remaining
# Join the data with raster-derived oxygen with the full cpue data
dat <- left_join(dat, big_dat_sub_temp2, by = "id_temp")
#> left_join: added one column (temp)
#> > rows only in x 0
#> > rows only in y ( 0)
#> > matched rows 8,570
#> > =======
#> > rows total 8,570
colnames(dat)
#> [1] "density" "year" "lat" "lon" "quarter"
#> [6] "haul.id" "IDx" "ices_rect" "sub_div" "density_fle"
#> [11] "depth" "id_oxy" "oxy" "id_temp" "temp"
dat <- dat %>% dplyr::select(-id_temp, -id_oxy)
# Drop NA temp
dat <- dat %>% drop_na(temp)
#> drop_na: no rows removed
# Now, if quarter == 1 in dat, temperature should be NA beucase I haven't done temperature for q1 here (see comment in the description of this script)
sort(unique(filter(dat, quarter == 1)$temp))
#> filter: removed 3,447 rows (40%), 5,123 rows remaining
#> [1] 2.816770 2.839721 2.962441 3.183795 3.217214 3.362540 3.388830
#> [8] 3.440997 3.487189 3.534348 3.537377 3.562383 3.573888 3.581972
#> [15] 3.608620 3.612902 3.617159 3.617956 3.626472 3.630720 3.631594
#> [22] 3.650912 3.669950 3.693239 3.698169 3.704681 3.707480 3.714890
#> [29] 3.730226 3.777852 3.778523 3.791405 3.791490 3.792335 3.802407
#> [36] 3.803586 3.819718 3.837321 3.842457 3.851959 3.894873 3.907859
#> [43] 3.909587 3.917520 3.921903 3.925696 3.933258 3.935552 3.943368
#> [50] 3.961727 3.967682 3.968158 3.975157 3.977777 3.980102 3.983644
#> [57] 3.986774 3.998888 3.999170 4.006690 4.006814 4.011684 4.012635
#> [64] 4.027484 4.030427 4.035700 4.038611 4.050009 4.050321 4.060131
#> [71] 4.069070 4.072324 4.076429 4.076640 4.093534 4.098957 4.100361
#> [78] 4.101202 4.111911 4.112977 4.114045 4.114869 4.118993 4.122699
#> [85] 4.124258 4.125990 4.129215 4.144033 4.145500 4.146676 4.150076
#> [92] 4.152376 4.154197 4.159016 4.159883 4.160406 4.165540 4.170450
#> [99] 4.172469 4.173786 4.175906 4.176355 4.177197 4.177969 4.181723
#> [106] 4.182795 4.183823 4.184236 4.184327 4.187502 4.188045 4.191886
#> [113] 4.192536 4.198551 4.200620 4.202079 4.202429 4.215802 4.219501
#> [120] 4.220352 4.221951 4.223564 4.224641 4.225915 4.226989 4.227474
#> [127] 4.230198 4.232364 4.241090 4.242667 4.246428 4.249261 4.254147
#> [134] 4.255640 4.259544 4.266747 4.268316 4.269372 4.270499 4.272568
#> [141] 4.274205 4.275863 4.278630 4.279246 4.284124 4.284404 4.288131
#> [148] 4.290457 4.294221 4.299889 4.302729 4.303256 4.314220 4.315154
#> [155] 4.315469 4.315796 4.318324 4.321654 4.323765 4.325264 4.333378
#> [162] 4.335189 4.339110 4.339444 4.341005 4.341107 4.341666 4.343083
#> [169] 4.343653 4.344322 4.352714 4.353508 4.356194 4.358324 4.363400
#> [176] 4.366299 4.367586 4.367861 4.369082 4.377148 4.381032 4.386201
#> [183] 4.387024 4.387345 4.391411 4.391558 4.392671 4.407523 4.408826
#> [190] 4.409272 4.413819 4.414574 4.416126 4.417572 4.418222 4.418281
#> [197] 4.419622 4.422520 4.431522 4.431537 4.432942 4.437119 4.437881
#> [204] 4.447785 4.448558 4.448971 4.449892 4.451333 4.451499 4.453301
#> [211] 4.455207 4.455904 4.457848 4.459081 4.463961 4.466003 4.474169
#> [218] 4.474288 4.476916 4.477868 4.480518 4.480971 4.483878 4.488875
#> [225] 4.491650 4.492449 4.494697 4.496325 4.497586 4.498228 4.498281
#> [232] 4.498672 4.500124 4.507144 4.507291 4.512174 4.512309 4.512974
#> [239] 4.513546 4.514152 4.516663 4.527128 4.528746 4.530585 4.533050
#> [246] 4.533987 4.534233 4.535123 4.537393 4.543230 4.545701 4.547534
#> [253] 4.548305 4.552804 4.554349 4.554404 4.561911 4.563087 4.567663
#> [260] 4.569046 4.574509 4.580757 4.584491 4.584927 4.588218 4.589489
#> [267] 4.590575 4.593273 4.594174 4.594419 4.594709 4.597927 4.606883
#> [274] 4.607244 4.607633 4.610949 4.611607 4.612518 4.623800 4.623965
#> [281] 4.625503 4.628160 4.630798 4.636961 4.639304 4.641683 4.646403
#> [288] 4.650682 4.651324 4.651843 4.655263 4.657221 4.657331 4.661943
#> [295] 4.662188 4.664516 4.665440 4.667027 4.668413 4.669485 4.674822
#> [302] 4.677519 4.677547 4.678653 4.679118 4.679431 4.679886 4.682072
#> [309] 4.685109 4.685434 4.685668 4.687873 4.688291 4.690118 4.691305
#> [316] 4.692845 4.693742 4.695752 4.698006 4.699983 4.707947 4.710910
#> [323] 4.711746 4.714057 4.716324 4.719533 4.725415 4.725508 4.727666
#> [330] 4.731587 4.735202 4.736112 4.740479 4.742999 4.743489 4.743898
#> [337] 4.744218 4.746395 4.747353 4.748975 4.751062 4.752277 4.752713
#> [344] 4.753339 4.756475 4.756783 4.758906 4.763341 4.767005 4.768158
#> [351] 4.770119 4.778391 4.778783 4.779663 4.781298 4.781523 4.782831
#> [358] 4.784300 4.785642 4.786974 4.788003 4.789741 4.789747 4.793939
#> [365] 4.794622 4.801650 4.801866 4.801993 4.803211 4.804157 4.811615
#> [372] 4.813532 4.816591 4.818445 4.820985 4.821183 4.822221 4.823396
#> [379] 4.827472 4.828284 4.830688 4.832346 4.832619 4.835987 4.838478
#> [386] 4.839241 4.841106 4.842165 4.842476 4.842512 4.842935 4.844587
#> [393] 4.847415 4.849226 4.850129 4.852528 4.853868 4.855977 4.856291
#> [400] 4.856291 4.858223 4.859437 4.860392 4.862360 4.864018 4.864212
#> [407] 4.865042 4.870034 4.873529 4.877180 4.877915 4.877984 4.880672
#> [414] 4.881296 4.884571 4.885864 4.886086 4.886356 4.888412 4.892872
#> [421] 4.894964 4.895291 4.895656 4.896533 4.898484 4.900525 4.905718
#> [428] 4.909171 4.909633 4.911920 4.915781 4.916227 4.916689 4.916777
#> [435] 4.918802 4.919593 4.919921 4.920233 4.922471 4.923398 4.923913
#> [442] 4.924510 4.925904 4.927632 4.927859 4.928835 4.929921 4.929962
#> [449] 4.930627 4.931291 4.931736 4.933319 4.934325 4.934346 4.938465
#> [456] 4.940901 4.940966 4.943095 4.944206 4.944956 4.946860 4.946943
#> [463] 4.949392 4.951283 4.952009 4.952495 4.955418 4.956209 4.956762
#> [470] 4.957189 4.962157 4.963048 4.967317 4.967474 4.968098 4.969739
#> [477] 4.970346 4.970408 4.972017 4.972071 4.976948 4.978970 4.979101
#> [484] 4.979337 4.983327 4.983888 4.984037 4.984814 4.986153 4.988389
#> [491] 4.989380 4.989484 4.991373 4.991603 4.991963 4.992329 4.994169
#> [498] 4.994317 4.998693 5.000540 5.001446 5.004096 5.004220 5.005444
#> [505] 5.006165 5.008710 5.009654 5.011030 5.011600 5.012346 5.013457
#> [512] 5.016551 5.019052 5.020233 5.020485 5.022298 5.025355 5.028135
#> [519] 5.028735 5.029204 5.030028 5.030389 5.032461 5.032723 5.032917
#> [526] 5.033372 5.033430 5.034256 5.036343 5.036586 5.037190 5.037380
#> [533] 5.037612 5.039335 5.041800 5.042625 5.043848 5.045337 5.048850
#> [540] 5.049138 5.053128 5.053373 5.053548 5.054082 5.055184 5.058304
#> [547] 5.059855 5.060612 5.062573 5.062845 5.065957 5.067118 5.068199
#> [554] 5.069317 5.070275 5.070469 5.070910 5.071182 5.075106 5.075657
#> [561] 5.076287 5.081142 5.083079 5.086201 5.086375 5.089163 5.089615
#> [568] 5.090286 5.090327 5.090937 5.090978 5.093029 5.093606 5.095536
#> [575] 5.096244 5.096336 5.100888 5.102343 5.103857 5.105870 5.106201
#> [582] 5.107653 5.107672 5.108706 5.109714 5.111314 5.111583 5.112233
#> [589] 5.114612 5.114795 5.118172 5.119134 5.119451 5.121054 5.122238
#> [596] 5.124387 5.126808 5.127109 5.127299 5.128732 5.131165 5.131665
#> [603] 5.134394 5.134756 5.137755 5.138518 5.141114 5.143019 5.144887
#> [610] 5.144916 5.145731 5.146524 5.154974 5.160484 5.161747 5.164114
#> [617] 5.165127 5.165421 5.165514 5.166508 5.167770 5.176141 5.178625
#> [624] 5.187901 5.188306 5.189782 5.189914 5.192542 5.195294 5.195784
#> [631] 5.197348 5.197471 5.198735 5.199663 5.203692 5.203769 5.208851
#> [638] 5.212655 5.214007 5.221703 5.222880 5.222892 5.223273 5.224087
#> [645] 5.224300 5.225695 5.226991 5.228296 5.232961 5.234176 5.234472
#> [652] 5.239223 5.240387 5.240856 5.241075 5.244443 5.244833 5.246146
#> [659] 5.247936 5.250791 5.251755 5.253927 5.254272 5.255830 5.257541
#> [666] 5.258648 5.262446 5.263240 5.266255 5.266387 5.268870 5.271112
#> [673] 5.271775 5.272003 5.275375 5.279538 5.281906 5.282355 5.283501
#> [680] 5.287220 5.289243 5.294972 5.296590 5.297019 5.297270 5.297643
#> [687] 5.298151 5.300921 5.301945 5.303112 5.305400 5.307615 5.309269
#> [694] 5.312838 5.314731 5.315160 5.322266 5.322581 5.322758 5.324059
#> [701] 5.326376 5.326639 5.327978 5.328394 5.328863 5.329261 5.330364
#> [708] 5.332611 5.333673 5.334006 5.335700 5.339123 5.343275 5.344022
#> [715] 5.345026 5.345602 5.347251 5.348242 5.357287 5.357375 5.358297
#> [722] 5.359321 5.361913 5.362691 5.363134 5.367559 5.368597 5.375740
#> [729] 5.377974 5.378153 5.378270 5.379675 5.379728 5.382415 5.384019
#> [736] 5.387121 5.388986 5.392056 5.394388 5.402484 5.405634 5.407827
#> [743] 5.408011 5.408677 5.410375 5.411544 5.411618 5.412321 5.414233
#> [750] 5.415058 5.415191 5.416467 5.417151 5.420528 5.423996 5.424533
#> [757] 5.425364 5.430250 5.435960 5.437160 5.438752 5.440060 5.443531
#> [764] 5.444339 5.445053 5.447474 5.447657 5.447748 5.451500 5.451992
#> [771] 5.453585 5.453688 5.462609 5.468419 5.471383 5.473356 5.474005
#> [778] 5.476027 5.476507 5.477591 5.477827 5.479754 5.482254 5.483072
#> [785] 5.483708 5.484193 5.484452 5.484599 5.485140 5.485350 5.485712
#> [792] 5.488230 5.488489 5.488532 5.490820 5.490908 5.491608 5.493072
#> [799] 5.495123 5.499329 5.499711 5.503320 5.503449 5.504573 5.505246
#> [806] 5.505450 5.506589 5.507218 5.507492 5.508654 5.509918 5.511411
#> [813] 5.512333 5.513602 5.515847 5.517428 5.518558 5.518917 5.519354
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#> [827] 5.532138 5.536137 5.541921 5.542039 5.542376 5.544172 5.545172
#> [834] 5.546176 5.549764 5.550932 5.552952 5.554749 5.560814 5.561349
#> [841] 5.562199 5.567733 5.568025 5.568344 5.568765 5.570472 5.571719
#> [848] 5.573438 5.578604 5.579824 5.581523 5.583483 5.584779 5.585278
#> [855] 5.587239 5.590873 5.590966 5.595365 5.596583 5.598294 5.602844
#> [862] 5.607010 5.607388 5.609790 5.610167 5.610638 5.613894 5.616286
#> [869] 5.620922 5.621299 5.628715 5.630046 5.630561 5.632282 5.632645
#> [876] 5.633468 5.634668 5.636521 5.641051 5.641882 5.643703 5.648070
#> [883] 5.649246 5.651548 5.652948 5.654208 5.656289 5.656481 5.657018
#> [890] 5.657026 5.657977 5.660972 5.661620 5.661708 5.661937 5.662486
#> [897] 5.663762 5.664887 5.667359 5.669425 5.669726 5.674425 5.674571
#> [904] 5.676809 5.676934 5.678760 5.680144 5.680973 5.682603 5.682684
#> [911] 5.683171 5.683908 5.685841 5.688407 5.691340 5.692239 5.693450
#> [918] 5.694981 5.695358 5.696163 5.697296 5.698485 5.698677 5.699909
#> [925] 5.700585 5.701982 5.702053 5.703937 5.704191 5.705019 5.709927
#> [932] 5.711621 5.714480 5.715194 5.716473 5.716481 5.718472 5.720527
#> [939] 5.720631 5.721321 5.721422 5.721547 5.721983 5.726427 5.726761
#> [946] 5.727661 5.727685 5.730689 5.732076 5.734318 5.735384 5.735991
#> [953] 5.738813 5.739212 5.740703 5.741584 5.743199 5.744425 5.745409
#> [960] 5.750276 5.750979 5.752042 5.753907 5.759260 5.761554 5.762009
#> [967] 5.762719 5.763182 5.764697 5.768596 5.769675 5.771676 5.774960
#> [974] 5.776127 5.779069 5.779239 5.780668 5.782426 5.785739 5.786218
#> [981] 5.791028 5.793658 5.795736 5.796091 5.797283 5.797947 5.800303
#> [988] 5.800652 5.801448 5.804265 5.806445 5.807315 5.807615 5.810804
#> [995] 5.810915 5.813216 5.815476 5.818113 5.819422 5.819683 5.823091
#> [1002] 5.831734 5.832649 5.834074 5.836293 5.836333 5.837493 5.845199
#> [1009] 5.846792 5.846888 5.847554 5.848777 5.849087 5.850218 5.851208
#> [1016] 5.852733 5.854263 5.855258 5.857920 5.858211 5.865470 5.865539
#> [1023] 5.875162 5.876291 5.878181 5.878331 5.882871 5.882959 5.883300
#> [1030] 5.885322 5.885927 5.886039 5.886808 5.888219 5.888343 5.888427
#> [1037] 5.888521 5.893198 5.893280 5.893928 5.893967 5.894387 5.894574
#> [1044] 5.895885 5.896451 5.897415 5.897501 5.900342 5.901719 5.902733
#> [1051] 5.903910 5.903917 5.905093 5.910266 5.910953 5.912163 5.912898
#> [1058] 5.917044 5.917392 5.918881 5.918968 5.921847 5.922917 5.925431
#> [1065] 5.926556 5.927853 5.927900 5.929958 5.933578 5.933808 5.934683
#> [1072] 5.935561 5.935830 5.936263 5.937224 5.940108 5.940292 5.943230
#> [1079] 5.946094 5.946551 5.948475 5.949252 5.950260 5.951290 5.951366
#> [1086] 5.953552 5.954073 5.958883 5.962306 5.962916 5.964534 5.965038
#> [1093] 5.966108 5.966647 5.971310 5.971325 5.973227 5.974376 5.976021
#> [1100] 5.976862 5.980159 5.984310 5.986950 5.987101 5.987347 5.987883
#> [1107] 5.988063 5.988729 5.994593 5.995021 5.996545 5.997107 5.997556
#> [1114] 6.000699 6.001531 6.004325 6.004914 6.005159 6.005203 6.006609
#> [1121] 6.007025 6.010594 6.010978 6.011240 6.011354 6.013360 6.013489
#> [1128] 6.014341 6.014823 6.016684 6.017108 6.019531 6.020870 6.022528
#> [1135] 6.022639 6.023544 6.024439 6.029997 6.030956 6.033872 6.034191
#> [1142] 6.034358 6.035449 6.036369 6.036734 6.037964 6.038929 6.039592
#> [1149] 6.041366 6.044076 6.047166 6.048625 6.053957 6.055316 6.055353
#> [1156] 6.055840 6.056051 6.056170 6.057319 6.057949 6.059443 6.059950
#> [1163] 6.061582 6.067111 6.072427 6.073650 6.074514 6.080604 6.082479
#> [1170] 6.082658 6.085110 6.087270 6.087277 6.088141 6.091613 6.092474
#> [1177] 6.096017 6.099216 6.102041 6.104620 6.105382 6.105873 6.106451
#> [1184] 6.107721 6.108429 6.110617 6.110898 6.111556 6.111696 6.111853
#> [1191] 6.112921 6.114684 6.117517 6.119624 6.119862 6.122731 6.123862
#> [1198] 6.124000 6.124195 6.124911 6.125554 6.128342 6.128492 6.128997
#> [1205] 6.129622 6.130042 6.130325 6.132073 6.132508 6.132732 6.133465
#> [1212] 6.134238 6.135283 6.139087 6.140545 6.141871 6.142052 6.146191
#> [1219] 6.146945 6.146953 6.147221 6.148468 6.148947 6.149760 6.150419
#> [1226] 6.152555 6.154879 6.155334 6.155885 6.158490 6.159183 6.160798
#> [1233] 6.161508 6.163272 6.164714 6.165203 6.165672 6.166927 6.167274
#> [1240] 6.168779 6.173032 6.173432 6.173518 6.173556 6.175330 6.177142
#> [1247] 6.177290 6.177909 6.177949 6.179605 6.181254 6.181612 6.182414
#> [1254] 6.183398 6.183690 6.186156 6.187075 6.189655 6.191375 6.191808
#> [1261] 6.191839 6.192175 6.192732 6.195284 6.197845 6.198173 6.198856
#> [1268] 6.199227 6.201395 6.203457 6.207046 6.208653 6.209286 6.210075
#> [1275] 6.210812 6.212916 6.215652 6.216448 6.217192 6.217982 6.218022
#> [1282] 6.218316 6.223654 6.229240 6.230494 6.230747 6.230788 6.233224
#> [1289] 6.233807 6.237158 6.240886 6.242289 6.242537 6.243241 6.243945
#> [1296] 6.245386 6.247582 6.249376 6.250483 6.250902 6.251322 6.252326
#> [1303] 6.254035 6.255763 6.258192 6.258444 6.258713 6.260383 6.260603
#> [1310] 6.261736 6.262338 6.262409 6.264708 6.265443 6.265636 6.268638
#> [1317] 6.269234 6.269523 6.269605 6.269977 6.270701 6.271803 6.273124
#> [1324] 6.273165 6.273320 6.273516 6.279624 6.280242 6.282084 6.283234
#> [1331] 6.283289 6.284028 6.285912 6.291101 6.294502 6.296846 6.297012
#> [1338] 6.297335 6.299077 6.299094 6.299148 6.306667 6.307087 6.307414
#> [1345] 6.309673 6.311340 6.313442 6.313501 6.313868 6.315989 6.317571
#> [1352] 6.318490 6.318576 6.320456 6.321329 6.324864 6.327215 6.328223
#> [1359] 6.329721 6.331779 6.333596 6.334531 6.334551 6.336109 6.336638
#> [1366] 6.343131 6.343912 6.345186 6.346045 6.347802 6.348607 6.348684
#> [1373] 6.349623 6.352775 6.353048 6.353553 6.353567 6.354010 6.354562
#> [1380] 6.354674 6.359671 6.360177 6.360739 6.361470 6.361546 6.364863
#> [1387] 6.365003 6.365655 6.367501 6.368102 6.368485 6.369676 6.370224
#> [1394] 6.372186 6.374384 6.377660 6.380534 6.382278 6.382787 6.383164
#> [1401] 6.383867 6.384284 6.384436 6.386008 6.386430 6.388581 6.393401
#> [1408] 6.394934 6.395188 6.397098 6.398055 6.398076 6.399123 6.399264
#> [1415] 6.400139 6.401664 6.401910 6.403418 6.405485 6.406282 6.407066
#> [1422] 6.407771 6.408742 6.411698 6.412775 6.413568 6.415561 6.415632
#> [1429] 6.419054 6.419402 6.419549 6.420934 6.421752 6.421771 6.422555
#> [1436] 6.425944 6.429135 6.432412 6.433446 6.434335 6.434862 6.435584
#> [1443] 6.437066 6.437136 6.437382 6.437621 6.438664 6.439194 6.442173
#> [1450] 6.442596 6.442911 6.444277 6.444730 6.446913 6.451279 6.452052
#> [1457] 6.453012 6.453527 6.454656 6.457224 6.462295 6.465171 6.467064
#> [1464] 6.468420 6.470227 6.472707 6.472779 6.476677 6.477878 6.478186
#> [1471] 6.478683 6.478959 6.479225 6.487972 6.488032 6.488691 6.489279
#> [1478] 6.489615 6.491682 6.494328 6.496209 6.496449 6.497931 6.497976
#> [1485] 6.498468 6.498551 6.499494 6.502265 6.502851 6.503233 6.504448
#> [1492] 6.506008 6.507005 6.507142 6.507335 6.507585 6.508314 6.509585
#> [1499] 6.510344 6.512323 6.512901 6.515875 6.517717 6.517738 6.519157
#> [1506] 6.523651 6.525319 6.526212 6.528250 6.529521 6.530211 6.531286
#> [1513] 6.532872 6.535895 6.539813 6.540287 6.541721 6.542053 6.542759
#> [1520] 6.545527 6.545865 6.549778 6.550356 6.551044 6.556732 6.557351
#> [1527] 6.559306 6.559647 6.561587 6.562147 6.562980 6.564571 6.564902
#> [1534] 6.565206 6.565396 6.567162 6.568058 6.572107 6.574119 6.574254
#> [1541] 6.574355 6.574603 6.574696 6.574729 6.574960 6.574980 6.575708
#> [1548] 6.576222 6.576878 6.577910 6.577955 6.582788 6.583389 6.584206
#> [1555] 6.585520 6.585927 6.586660 6.587323 6.587522 6.588920 6.589430
#> [1562] 6.591107 6.592505 6.592950 6.594999 6.596712 6.598809 6.600846
#> [1569] 6.602346 6.604936 6.605970 6.606158 6.606936 6.608612 6.608770
#> [1576] 6.609228 6.609316 6.610117 6.611307 6.611917 6.612801 6.614425
#> [1583] 6.615016 6.615792 6.616018 6.616022 6.616183 6.616251 6.616433
#> [1590] 6.616752 6.617298 6.617363 6.619718 6.624300 6.624413 6.627281
#> [1597] 6.628502 6.628509 6.630895 6.632353 6.632375 6.633456 6.634544
#> [1604] 6.635009 6.638959 6.640116 6.640745 6.641278 6.641333 6.645274
#> [1611] 6.646369 6.646381 6.647337 6.648653 6.649552 6.649912 6.654005
#> [1618] 6.657989 6.658078 6.659413 6.662173 6.662974 6.667538 6.668051
#> [1625] 6.668970 6.673716 6.673995 6.674250 6.678208 6.682206 6.682675
#> [1632] 6.684578 6.685060 6.687457 6.688074 6.688373 6.689534 6.689790
#> [1639] 6.691371 6.692060 6.693266 6.693662 6.696969 6.698787 6.699268
#> [1646] 6.700742 6.702245 6.703024 6.705516 6.706081 6.707294 6.707506
#> [1653] 6.708904 6.709625 6.713574 6.717166 6.717773 6.719939 6.721448
#> [1660] 6.723029 6.723843 6.726017 6.728927 6.729335 6.730899 6.730923
#> [1667] 6.732810 6.734710 6.735347 6.735562 6.737897 6.738725 6.739515
#> [1674] 6.740031 6.742176 6.742247 6.742670 6.743677 6.744563 6.744984
#> [1681] 6.745424 6.746135 6.748135 6.748293 6.748450 6.749502 6.750049
#> [1688] 6.752369 6.754314 6.756365 6.759336 6.764150 6.770541 6.771767
#> [1695] 6.772518 6.774311 6.774701 6.775313 6.776182 6.776387 6.778559
#> [1702] 6.778888 6.780940 6.781282 6.781599 6.784131 6.787670 6.788186
#> [1709] 6.791794 6.792283 6.793113 6.793152 6.794015 6.795228 6.797145
#> [1716] 6.799208 6.800854 6.801832 6.802313 6.804261 6.805164 6.806061
#> [1723] 6.806173 6.808252 6.808997 6.809314 6.811613 6.813649 6.814677
#> [1730] 6.816426 6.817658 6.818876 6.819640 6.821267 6.822241 6.824118
#> [1737] 6.824450 6.824983 6.827919 6.828811 6.830193 6.833449 6.837315
#> [1744] 6.838359 6.839319 6.840577 6.840872 6.841090 6.841115 6.842668
#> [1751] 6.842896 6.843588 6.844125 6.844578 6.844732 6.844937 6.846114
#> [1758] 6.848179 6.848607 6.849557 6.849827 6.851722 6.851751 6.853623
#> [1765] 6.854449 6.857454 6.857601 6.858829 6.859604 6.860526 6.862350
#> [1772] 6.862417 6.865530 6.866139 6.867472 6.869528 6.877463 6.877986
#> [1779] 6.878452 6.881465 6.881838 6.888209 6.889309 6.889505 6.889829
#> [1786] 6.890255 6.890635 6.894597 6.896612 6.898356 6.900576 6.903078
#> [1793] 6.905293 6.906356 6.907022 6.907217 6.909298 6.909858 6.909858
#> [1800] 6.911827 6.913471 6.914478 6.914546 6.915585 6.917128 6.919894
#> [1807] 6.921732 6.922652 6.924088 6.929685 6.931822 6.934281 6.936270
#> [1814] 6.937945 6.938596 6.940307 6.942481 6.944215 6.945933 6.946718
#> [1821] 6.948301 6.952507 6.956458 6.960577 6.961063 6.962347 6.963194
#> [1828] 6.964898 6.965913 6.966936 6.969302 6.970125 6.971057 6.972544
#> [1835] 6.976151 6.982678 6.982979 6.985246 6.985543 6.987051 6.987264
#> [1842] 6.987666 6.990329 6.992094 6.992134 6.994094 6.994902 6.995465
#> [1849] 6.995743 6.996509 6.996726 6.996927 6.997181 6.997365 7.001432
#> [1856] 7.001490 7.001689 7.001768 7.006908 7.007252 7.007818 7.011683
#> [1863] 7.011921 7.011949 7.012527 7.012573 7.012579 7.012775 7.013117
#> [1870] 7.016888 7.017434 7.018286 7.020684 7.021576 7.023627 7.024469
#> [1877] 7.025786 7.027087 7.028354 7.028780 7.030837 7.031772 7.031910
#> [1884] 7.032109 7.032186 7.035573 7.036129 7.036833 7.038937 7.039182
#> [1891] 7.041563 7.041572 7.041957 7.042814 7.045539 7.045559 7.045739
#> [1898] 7.053181 7.053397 7.054484 7.054911 7.055033 7.055164 7.056125
#> [1905] 7.057342 7.057460 7.057691 7.062449 7.062599 7.063272 7.064511
#> [1912] 7.066280 7.068359 7.069244 7.069746 7.069755 7.070149 7.071548
#> [1919] 7.073025 7.073914 7.074090 7.075486 7.076722 7.077671 7.078147
#> [1926] 7.078442 7.081659 7.082075 7.082184 7.084642 7.085436 7.085790
#> [1933] 7.086781 7.087021 7.088586 7.090564 7.091546 7.092720 7.093829
#> [1940] 7.094640 7.098489 7.100806 7.100995 7.102221 7.103488 7.103596
#> [1947] 7.105703 7.105997 7.106064 7.107111 7.109522 7.109792 7.110680
#> [1954] 7.110955 7.111659 7.112068 7.114908 7.116359 7.116810 7.116926
#> [1961] 7.116964 7.117016 7.118487 7.119578 7.126952 7.127130 7.128836
#> [1968] 7.129794 7.130218 7.131452 7.132646 7.134913 7.138113 7.138946
#> [1975] 7.142807 7.143031 7.143843 7.143973 7.144026 7.145340 7.147428
#> [1982] 7.148479 7.149737 7.150647 7.152431 7.154226 7.155439 7.155585
#> [1989] 7.158215 7.160456 7.160576 7.160644 7.160846 7.163309 7.164848
#> [1996] 7.168409 7.169671 7.170244 7.172100 7.173128 7.175834 7.177708
#> [2003] 7.177993 7.180995 7.182436 7.183088 7.188402 7.188805 7.189467
#> [2010] 7.189987 7.191588 7.191796 7.193357 7.196866 7.198750 7.199057
#> [2017] 7.201687 7.202771 7.204878 7.205909 7.205989 7.207481 7.208614
#> [2024] 7.210038 7.210286 7.210361 7.212841 7.214236 7.219993 7.220087
#> [2031] 7.220348 7.222233 7.223635 7.225535 7.226877 7.229675 7.233800
#> [2038] 7.237353 7.237506 7.237969 7.238278 7.239209 7.239962 7.241487
#> [2045] 7.243091 7.244790 7.245076 7.245969 7.246197 7.247871 7.248577
#> [2052] 7.249153 7.249684 7.254649 7.256575 7.257167 7.258296 7.262325
#> [2059] 7.262448 7.265189 7.265977 7.271284 7.273910 7.278051 7.280339
#> [2066] 7.281562 7.282598 7.282822 7.283930 7.284427 7.285732 7.286525
#> [2073] 7.287686 7.291969 7.293759 7.295015 7.297935 7.298634 7.300008
#> [2080] 7.300069 7.302709 7.304412 7.306429 7.308523 7.309129 7.310778
#> [2087] 7.312214 7.315098 7.316043 7.317705 7.318591 7.318644 7.319521
#> [2094] 7.323926 7.324019 7.325888 7.326732 7.328297 7.329094 7.333109
#> [2101] 7.333155 7.333685 7.334612 7.334794 7.336366 7.336607 7.336735
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#> [2122] 7.353416 7.355685 7.356584 7.356903 7.358463 7.360562 7.360611
#> [2129] 7.360953 7.363813 7.365408 7.367135 7.367332 7.367842 7.367883
#> [2136] 7.369623 7.370701 7.372540 7.372916 7.377543 7.377995 7.378140
#> [2143] 7.378891 7.382170 7.384165 7.385073 7.385733 7.385932 7.386643
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#> [2157] 7.392664 7.393098 7.393799 7.396415 7.400325 7.401368 7.401907
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#> [2227] 7.489054 7.490517 7.491624 7.492250 7.494380 7.497012 7.498158
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#> [2241] 7.507788 7.508826 7.510796 7.510929 7.517392 7.522179 7.522543
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#> [2318] 7.643878 7.644432 7.645140 7.645445 7.646086 7.646796 7.647896
#> [2325] 7.649358 7.651795 7.652253 7.653235 7.655162 7.656824 7.662454
#> [2332] 7.664417 7.664584 7.664691 7.667243 7.667586 7.669306 7.670435
#> [2339] 7.671440 7.671948 7.672173 7.672649 7.672871 7.674200 7.674953
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#> [2353] 7.683542 7.685024 7.685228 7.685497 7.685514 7.686312 7.686674
#> [2360] 7.687933 7.688824 7.689449 7.690344 7.690628 7.691364 7.692940
#> [2367] 7.693113 7.693294 7.699753 7.701466 7.702434 7.703460 7.703836
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#> [2388] 7.726225 7.727218 7.727322 7.727923 7.728253 7.728513 7.729176
#> [2395] 7.729424 7.732148 7.733660 7.733795 7.733842 7.735003 7.735032
#> [2402] 7.736092 7.736331 7.736745 7.739364 7.740688 7.741634 7.742114
#> [2409] 7.743912 7.747246 7.747682 7.750407 7.751762 7.754528 7.755297
#> [2416] 7.758511 7.759037 7.759650 7.759742 7.760760 7.762855 7.764109
#> [2423] 7.766173 7.766422 7.766569 7.766729 7.766820 7.767568 7.772022
#> [2430] 7.773869 7.778874 7.780770 7.780815 7.780963 7.783341 7.784039
#> [2437] 7.785301 7.788435 7.788836 7.790183 7.790911 7.792727 7.793499
#> [2444] 7.794406 7.795187 7.795707 7.796605 7.796744 7.802504 7.802771
#> [2451] 7.807389 7.808609 7.808662 7.809903 7.810702 7.814849 7.815211
#> [2458] 7.816638 7.816824 7.817260 7.820370 7.823358 7.825809 7.827474
#> [2465] 7.828731 7.829191 7.831487 7.832124 7.832706 7.834208 7.834574
#> [2472] 7.836455 7.839158 7.842660 7.845474 7.846043 7.847968 7.849943
#> [2479] 7.852384 7.852814 7.853252 7.854025 7.855452 7.857213 7.858522
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#> [2493] 7.873302 7.873565 7.873845 7.876333 7.876602 7.878484 7.879503
#> [2500] 7.881294 7.881442 7.882213 7.882407 7.886458 7.888667 7.889744
#> [2507] 7.891154 7.892132 7.894531 7.901143 7.902113 7.902554 7.904194
#> [2514] 7.907438 7.909010 7.910369 7.910413 7.911892 7.912679 7.913965
#> [2521] 7.914340 7.914686 7.914768 7.915765 7.916861 7.917127 7.918544
#> [2528] 7.919207 7.919717 7.921749 7.922159 7.922363 7.923646 7.923852
#> [2535] 7.926567 7.926984 7.930511 7.932551 7.932629 7.933643 7.935150
#> [2542] 7.936161 7.937817 7.938524 7.940608 7.941026 7.941179 7.942680
#> [2549] 7.943109 7.944372 7.944652 7.947571 7.948221 7.948249 7.950717
#> [2556] 7.954545 7.954554 7.954558 7.954685 7.957141 7.957974 7.959555
#> [2563] 7.963620 7.965783 7.966304 7.968513 7.970912 7.974137 7.974270
#> [2570] 7.977654 7.978186 7.978686 7.979941 7.980332 7.980492 7.984234
#> [2577] 7.985000 7.985874 7.986879 7.988233 7.994156 7.994389 7.994712
#> [2584] 7.995543 7.997733 7.997989 7.999346 8.000926 8.004114 8.004669
#> [2591] 8.004872 8.006395 8.007272 8.007594 8.008201 8.015943 8.016372
#> [2598] 8.016915 8.017432 8.019953 8.020535 8.021107 8.021956 8.022501
#> [2605] 8.024339 8.024958 8.026966 8.027728 8.028065 8.028988 8.029543
#> [2612] 8.030327 8.032805 8.034120 8.035660 8.036307 8.039160 8.046071
#> [2619] 8.046575 8.046952 8.047944 8.050173 8.051025 8.051744 8.056706
#> [2626] 8.057066 8.057784 8.059923 8.060260 8.061775 8.062768 8.063368
#> [2633] 8.065090 8.065716 8.066442 8.067012 8.067257 8.067531 8.068277
#> [2640] 8.069643 8.069778 8.070194 8.071779 8.072319 8.074618 8.075480
#> [2647] 8.075598 8.076142 8.076324 8.077884 8.078622 8.080841 8.083634
#> [2654] 8.084469 8.085117 8.085119 8.085633 8.085873 8.086159 8.086386
#> [2661] 8.086688 8.086842 8.087149 8.088066 8.090918 8.094558 8.095528
#> [2668] 8.097246 8.097524 8.097603 8.098669 8.100405 8.101576 8.101920
#> [2675] 8.102386 8.103745 8.105899 8.106540 8.111563 8.113792 8.116136
#> [2682] 8.116709 8.117289 8.117475 8.118815 8.118846 8.119862 8.120378
#> [2689] 8.124612 8.125507 8.129514 8.130470 8.131613 8.134414 8.134936
#> [2696] 8.135124 8.139163 8.139899 8.140759 8.141175 8.142250 8.143859
#> [2703] 8.143979 8.144574 8.144595 8.146239 8.146957 8.147652 8.148547
#> [2710] 8.148844 8.149899 8.150535 8.159068 8.160565 8.163596 8.168116
#> [2717] 8.168479 8.168571 8.171360 8.172207 8.173392 8.173518 8.173759
#> [2724] 8.174144 8.175397 8.175520 8.176283 8.176572 8.177046 8.177114
#> [2731] 8.177389 8.178402 8.179620 8.180639 8.181522 8.181574 8.182849
#> [2738] 8.185649 8.185846 8.186348 8.194452 8.197742 8.197882 8.200156
#> [2745] 8.206171 8.207865 8.208651 8.209066 8.211174 8.211297 8.212916
#> [2752] 8.213864 8.215763 8.217127 8.219747 8.221647 8.223401 8.224084
#> [2759] 8.224574 8.225269 8.225497 8.226667 8.227940 8.228801 8.232008
#> [2766] 8.233421 8.234017 8.238335 8.240622 8.243187 8.244994 8.249211
#> [2773] 8.252031 8.252283 8.252772 8.253313 8.253368 8.253463 8.254768
#> [2780] 8.254817 8.256017 8.256780 8.257226 8.258942 8.259610 8.259882
#> [2787] 8.263266 8.263289 8.265087 8.265736 8.266293 8.268305 8.271089
#> [2794] 8.273618 8.275047 8.275544 8.278131 8.279282 8.279313 8.279402
#> [2801] 8.279739 8.283282 8.286797 8.287415 8.287616 8.294419 8.294939
#> [2808] 8.296482 8.297923 8.298692 8.298997 8.302004 8.302387 8.302747
#> [2815] 8.302981 8.303348 8.303685 8.304511 8.305696 8.306604 8.307133
#> [2822] 8.307758 8.310491 8.312519 8.312556 8.314226 8.314484 8.315935
#> [2829] 8.319754 8.322836 8.323098 8.324632 8.324683 8.324728 8.325344
#> [2836] 8.325440 8.328288 8.328961 8.332228 8.334354 8.335124 8.335419
#> [2843] 8.336419 8.337694 8.337747 8.341959 8.342462 8.344117 8.344653
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#> [2857] 8.352670 8.353391 8.353640 8.354530 8.356452 8.356631 8.358658
#> [2864] 8.358731 8.358909 8.359003 8.359658 8.360498 8.367199 8.368703
#> [2871] 8.368973 8.369227 8.370124 8.370603 8.371640 8.372114 8.372327
#> [2878] 8.372922 8.374687 8.378025 8.379349 8.379623 8.380312 8.380807
#> [2885] 8.380809 8.383134 8.383360 8.386858 8.387093 8.388429 8.388591
#> [2892] 8.390859 8.394312 8.394888 8.397312 8.397519 8.398695 8.398710
#> [2899] 8.398729 8.401249 8.405033 8.405084 8.408405 8.409457 8.409830
#> [2906] 8.412490 8.412834 8.413391 8.417647 8.418877 8.419026 8.419250
#> [2913] 8.420054 8.422451 8.423481 8.423868 8.424205 8.425543 8.425543
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#> [2927] 8.435944 8.440470 8.440928 8.443145 8.443320 8.444139 8.446935
#> [2934] 8.449001 8.450069 8.450201 8.450258 8.450313 8.455484 8.457123
#> [2941] 8.457611 8.458650 8.460930 8.463682 8.464397 8.466096 8.466463
#> [2948] 8.467528 8.468637 8.468896 8.469294 8.469519 8.469889 8.473714
#> [2955] 8.474380 8.477197 8.477458 8.477520 8.477843 8.478236 8.479451
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#> [2969] 8.493114 8.493857 8.496386 8.504403 8.504421 8.507071 8.507898
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#> [2983] 8.510370 8.511731 8.512043 8.512324 8.513200 8.513397 8.515713
#> [2990] 8.515891 8.518596 8.520289 8.521041 8.521874 8.523684 8.524567
#> [2997] 8.524921 8.525522 8.526633 8.528198 8.530657 8.530971 8.531177
#> [3004] 8.531464 8.531994 8.532286 8.536041 8.536710 8.536892 8.538392
#> [3011] 8.538675 8.542109 8.542579 8.542867 8.544340 8.546542 8.548198
#> [3018] 8.548710 8.548761 8.550190 8.551553 8.552230 8.556820 8.557137
#> [3025] 8.557321 8.557693 8.557894 8.561448 8.563604 8.564635 8.565757
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#> [3039] 8.582543 8.583111 8.584092 8.586082 8.586951 8.587212 8.587523
#> [3046] 8.588590 8.589683 8.589692 8.591013 8.592072 8.593268 8.596362
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#> [3060] 8.602316 8.602520 8.602802 8.602886 8.603611 8.605011 8.605549
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#> [3088] 8.654144 8.655731 8.656000 8.656887 8.658961 8.661206 8.661239
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#> [3109] 8.681042 8.682691 8.682822 8.682923 8.684140 8.684807 8.687847
#> [3116] 8.689622 8.689891 8.690277 8.690914 8.691826 8.692581 8.692621
#> [3123] 8.693925 8.693990 8.694296 8.695167 8.696652 8.698179 8.702157
#> [3130] 8.705973 8.706084 8.706872 8.706968 8.707409 8.707947 8.708525
#> [3137] 8.708597 8.709167 8.711314 8.713013 8.713973 8.714754 8.715081
#> [3144] 8.716086 8.718446 8.719187 8.719822 8.720144 8.721864 8.722987
#> [3151] 8.723674 8.725006 8.726671 8.728109 8.730174 8.731812 8.734194
#> [3158] 8.735024 8.736502 8.737386 8.737573 8.738080 8.738260 8.739378
#> [3165] 8.740809 8.741363 8.742356 8.743003 8.746024 8.746713 8.752383
#> [3172] 8.752414 8.757695 8.757713 8.758000 8.762150 8.762359 8.764428
#> [3179] 8.766935 8.767569 8.768111 8.768688 8.768904 8.769913 8.770060
#> [3186] 8.771328 8.771698 8.771959 8.772210 8.772425 8.772449 8.772610
#> [3193] 8.775057 8.775190 8.775909 8.778771 8.778832 8.779073 8.779216
#> [3200] 8.781475 8.781614 8.784657 8.786253 8.787163 8.787535 8.788068
#> [3207] 8.789546 8.790648 8.791455 8.792149 8.792249 8.794226 8.794968
#> [3214] 8.796587 8.798499 8.800814 8.801341 8.801853 8.804091 8.804692
#> [3221] 8.804782 8.805306 8.806584 8.806842 8.807308 8.808661 8.809223
#> [3228] 8.809238 8.809888 8.812242 8.812679 8.814527 8.817764 8.817985
#> [3235] 8.819123 8.819248 8.819871 8.819967 8.821241 8.821425 8.821757
#> [3242] 8.824510 8.825161 8.825168 8.825226 8.827870 8.828335 8.830452
#> [3249] 8.831148 8.831790 8.831899 8.837706 8.841365 8.849537 8.850386
#> [3256] 8.850609 8.852285 8.852559 8.857871 8.858784 8.858907 8.858985
#> [3263] 8.860205 8.862198 8.863042 8.863437 8.865959 8.866601 8.866918
#> [3270] 8.867968 8.870958 8.871312 8.872491 8.873553 8.873990 8.874335
#> [3277] 8.878146 8.879562 8.882257 8.883402 8.884479 8.885648 8.886458
#> [3284] 8.886969 8.890741 8.891009 8.892939 8.894097 8.895558 8.901606
#> [3291] 8.903539 8.903687 8.903803 8.914588 8.915154 8.918817 8.918920
#> [3298] 8.920175 8.924330 8.925837 8.927145 8.927286 8.929045 8.930565
#> [3305] 8.930673 8.931452 8.932323 8.934412 8.936242 8.936439 8.936536
#> [3312] 8.946330 8.947224 8.947352 8.949149 8.949454 8.951197 8.953097
#> [3319] 8.953239 8.953242 8.953258 8.955384 8.955387 8.956321 8.959618
#> [3326] 8.963306 8.966069 8.967244 8.982960 8.983442 8.992057 8.994666
#> [3333] 8.996570 8.997889 8.999893 9.001521 9.003228 9.004517 9.005555
#> [3340] 9.007884 9.010992 9.011318 9.011858 9.012697 9.014836 9.020796
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#> [3361] 9.043045 9.043466 9.048905 9.053060 9.053864 9.054017 9.054914
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#> [3403] 9.107068 9.107772 9.108627 9.109468 9.111533 9.111787 9.112965
#> [3410] 9.113065 9.120565 9.121580 9.123450 9.123459 9.125478 9.125911
#> [3417] 9.126306 9.127687 9.131424 9.132571 9.132708 9.133048 9.135222
#> [3424] 9.138896 9.139462 9.139832 9.140914 9.141803 9.141962 9.143184
#> [3431] 9.144211 9.144451 9.144830 9.145475 9.150115 9.152487 9.154031
#> [3438] 9.158916 9.161665 9.162264 9.163520 9.169503 9.177076 9.177847
#> [3445] 9.180149 9.180599 9.181637 9.183683 9.184488 9.185189 9.185248
#> [3452] 9.186523 9.187950 9.188647 9.188994 9.191258 9.191392 9.192181
#> [3459] 9.192599 9.193021 9.194786 9.200523 9.203219 9.204889 9.205741
#> [3466] 9.206198 9.207442 9.208543 9.210761 9.214128 9.214477 9.215920
#> [3473] 9.216568 9.216650 9.220246 9.221538 9.233181 9.234467 9.235644
#> [3480] 9.238631 9.238946 9.239426 9.239978 9.240968 9.241235 9.242171
#> [3487] 9.245416 9.246542 9.248638 9.249278 9.249860 9.251572 9.252405
#> [3494] 9.254226 9.255902 9.259306 9.262429 9.262978 9.263288 9.264599
#> [3501] 9.264872 9.266562 9.266732 9.266869 9.268467 9.270249 9.270642
#> [3508] 9.275162 9.275464 9.279437 9.280036 9.287067 9.288928 9.289035
#> [3515] 9.294615 9.301726 9.303843 9.304018 9.304445 9.305739 9.307017
#> [3522] 9.309619 9.311311 9.311930 9.313810 9.315578 9.318051 9.321762
#> [3529] 9.322576 9.323398 9.324017 9.324087 9.324242 9.326095 9.327418
#> [3536] 9.330037 9.331622 9.332246 9.334321 9.335316 9.335519 9.337209
#> [3543] 9.337466 9.337690 9.339652 9.341067 9.344530 9.345127 9.346191
#> [3550] 9.348519 9.349416 9.349683 9.352501 9.352938 9.353043 9.353541
#> [3557] 9.359464 9.359630 9.359650 9.363383 9.365148 9.368315 9.371220
#> [3564] 9.374624 9.374948 9.377109 9.377971 9.378178 9.379754 9.381693
#> [3571] 9.382291 9.382345 9.385180 9.386262 9.387348 9.390141 9.397201
#> [3578] 9.398847 9.402783 9.404580 9.405248 9.406570 9.408183 9.408371
#> [3585] 9.409081 9.409763 9.411352 9.412421 9.412990 9.415298 9.416126
#> [3592] 9.418165 9.418373 9.418502 9.418902 9.420746 9.423039 9.423196
#> [3599] 9.425716 9.426695 9.428263 9.430306 9.431911 9.433128 9.433493
#> [3606] 9.433675 9.435431 9.436317 9.436945 9.437364 9.437983 9.438127
#> [3613] 9.438526 9.440393 9.441593 9.441799 9.443704 9.447620 9.449206
#> [3620] 9.452117 9.453114 9.455301 9.459651 9.461951 9.465089 9.467795
#> [3627] 9.468171 9.469264 9.470969 9.477223 9.480664 9.482772 9.483795
#> [3634] 9.485391 9.486014 9.486321 9.489404 9.489944 9.490233 9.492681
#> [3641] 9.496011 9.497169 9.499125 9.500749 9.504457 9.504892 9.505078
#> [3648] 9.505087 9.505863 9.505984 9.506207 9.507690 9.508444 9.510171
#> [3655] 9.510973 9.512926 9.513787 9.514347 9.515117 9.517796 9.522779
#> [3662] 9.524507 9.526783 9.528484 9.529728 9.530244 9.532654 9.532704
#> [3669] 9.532800 9.533883 9.534639 9.535474 9.535739 9.536180 9.536591
#> [3676] 9.537515 9.538479 9.540038 9.541983 9.542156 9.544635 9.544679
#> [3683] 9.545396 9.546933 9.548594 9.549980 9.552657 9.556422 9.559037
#> [3690] 9.561096 9.561574 9.564144 9.564226 9.564287 9.566717 9.566913
#> [3697] 9.566969 9.568556 9.570863 9.573073 9.574871 9.576104 9.576402
#> [3704] 9.577571 9.582508 9.585769 9.585896 9.589971 9.591671 9.593182
#> [3711] 9.594119 9.595402 9.595966 9.597068 9.599294 9.600102 9.600283
#> [3718] 9.601390 9.601519 9.602183 9.603024 9.603815 9.604347 9.607638
#> [3725] 9.608414 9.610172 9.610287 9.611227 9.611365 9.611614 9.612196
#> [3732] 9.618519 9.618551 9.618925 9.621584 9.623028 9.623905 9.625812
#> [3739] 9.626103 9.626582 9.628302 9.628892 9.630497 9.632914 9.633439
#> [3746] 9.636594 9.639550 9.641929 9.645085 9.646546 9.650805 9.651873
#> [3753] 9.652828 9.653627 9.654357 9.655235 9.656666 9.657003 9.657135
#> [3760] 9.658672 9.658810 9.659624 9.660675 9.660838 9.661708 9.662812
#> [3767] 9.662878 9.663997 9.664614 9.667050 9.670107 9.671353 9.672492
#> [3774] 9.672680 9.673363 9.675562 9.678486 9.678693 9.681002 9.683952
#> [3781] 9.687172 9.687280 9.688255 9.690073 9.692477 9.693470 9.693886
#> [3788] 9.694385 9.696242 9.698114 9.698505 9.700473 9.701354 9.701669
#> [3795] 9.705940 9.706169 9.707551 9.707939 9.709684 9.714053 9.714313
#> [3802] 9.716443 9.717666 9.717881 9.719552 9.721801 9.722967 9.729912
#> [3809] 9.733214 9.737486 9.738328 9.740374 9.741173 9.741338 9.742270
#> [3816] 9.742791 9.742879 9.743085 9.746831 9.749014 9.749289 9.749662
#> [3823] 9.753275 9.757091 9.760473 9.761489 9.761535 9.763331 9.764498
#> [3830] 9.765695 9.775126 9.776074 9.776972 9.778874 9.780686 9.788313
#> [3837] 9.791772 9.793297 9.795744 9.796550 9.796597 9.796870 9.799242
#> [3844] 9.799395 9.806108 9.806756 9.809249 9.810236 9.811321 9.811500
#> [3851] 9.811503 9.811954 9.813417 9.814318 9.819411 9.821074 9.822583
#> [3858] 9.825477 9.831233 9.834249 9.834915 9.835649 9.837872 9.838604
#> [3865] 9.839568 9.840116 9.847120 9.847490 9.847583 9.851002 9.851138
#> [3872] 9.853584 9.854344 9.855724 9.855920 9.858510 9.859098 9.859383
#> [3879] 9.863341 9.863889 9.864108 9.868068 9.869473 9.870055 9.870827
#> [3886] 9.870946 9.872217 9.873499 9.873651 9.878285 9.879115 9.882313
#> [3893] 9.882759 9.883951 9.885595 9.887850 9.888651 9.888903 9.889629
#> [3900] 9.890327 9.890879 9.893315 9.896916 9.897218 9.898301 9.899842
#> [3907] 9.901243 9.903822 9.904309 9.905005 9.905300 9.905894 9.913742
#> [3914] 9.915136 9.918424 9.918620 9.918632 9.919636 9.920644 9.921957
#> [3921] 9.922091 9.922233 9.922442 9.922918 9.925569 9.929720 9.930230
#> [3928] 9.932503 9.933887 9.934282 9.934609 9.934614 9.936026 9.937246
#> [3935] 9.940583 9.941430 9.942097 9.944116 9.945934 9.946345 9.949342
#> [3942] 9.951872 9.953034 9.953592 9.954364 9.954794 9.955813 9.955987
#> [3949] 9.961829 9.962506 9.965292 9.966165 9.966192 9.975844 9.977726
#> [3956] 9.979640 9.980234 9.980586 9.981841 9.982583 9.985658 9.986535
#> [3963] 9.990476 9.990992 9.992421 9.993106 9.995431 10.000039 10.002675
#> [3970] 10.003290 10.004888 10.005432 10.006902 10.008977 10.012440 10.012694
#> [3977] 10.014406 10.014420 10.016777 10.023241 10.024608 10.024629 10.027002
#> [3984] 10.029761 10.030706 10.032806 10.038277 10.039075 10.043698 10.044404
#> [3991] 10.050039 10.050774 10.052935 10.053207 10.055287 10.056014 10.056932
#> [3998] 10.057707 10.058676 10.065144 10.066984 10.068505 10.071595 10.074035
#> [4005] 10.074528 10.079856 10.082153 10.082531 10.083148 10.084418 10.088007
#> [4012] 10.091193 10.096524 10.097570 10.104020 10.105188 10.107192 10.108173
#> [4019] 10.109714 10.110504 10.111135 10.114401 10.118485 10.122703 10.124766
#> [4026] 10.128760 10.129520 10.132243 10.133747 10.134235 10.134328 10.134647
#> [4033] 10.136336 10.136739 10.137105 10.137858 10.140954 10.143075 10.150328
#> [4040] 10.150623 10.153654 10.154428 10.155664 10.157901 10.158256 10.161330
#> [4047] 10.166446 10.167411 10.167513 10.169656 10.169746 10.173733 10.174023
#> [4054] 10.177763 10.179230 10.179511 10.180757 10.181383 10.182691 10.183758
#> [4061] 10.184466 10.186427 10.187478 10.187589 10.191344 10.192729 10.195542
#> [4068] 10.196198 10.198973 10.199821 10.204004 10.207153 10.213043 10.213273
#> [4075] 10.214332 10.215288 10.217933 10.218925 10.219837 10.220023 10.222067
#> [4082] 10.222227 10.222331 10.222530 10.223941 10.225293 10.226002 10.226717
#> [4089] 10.228552 10.229151 10.230148 10.231145 10.232602 10.232960 10.239774
#> [4096] 10.240571 10.242052 10.244116 10.245714 10.248159 10.248599 10.248832
#> [4103] 10.250593 10.251328 10.253291 10.253645 10.257366 10.257526 10.258939
#> [4110] 10.265215 10.266105 10.266697 10.270163 10.272482 10.273326 10.274911
#> [4117] 10.278484 10.278605 10.281725 10.286182 10.287109 10.293114 10.293285
#> [4124] 10.293851 10.297558 10.302269 10.303611 10.304248 10.307397 10.313504
#> [4131] 10.315547 10.316282 10.317190 10.317627 10.317751 10.319361 10.320392
#> [4138] 10.320887 10.321304 10.323271 10.326661 10.327507 10.327623 10.332427
#> [4145] 10.334451 10.335375 10.337234 10.339693 10.346205 10.346504 10.347866
#> [4152] 10.355275 10.356351 10.361894 10.363263 10.367893 10.372583 10.373804
#> [4159] 10.373866 10.375290 10.375814 10.376646 10.378090 10.379558 10.383235
#> [4166] 10.385892 10.387299 10.388097 10.389153 10.389650 10.389973 10.392129
#> [4173] 10.392401 10.392493 10.392661 10.396728 10.397065 10.400957 10.404045
#> [4180] 10.404507 10.406665 10.408833 10.412038 10.412826 10.414167 10.415381
#> [4187] 10.417115 10.417923 10.418770 10.419623 10.420972 10.421010 10.429719
#> [4194] 10.434390 10.436532 10.436598 10.440955 10.443786 10.445876 10.445930
#> [4201] 10.450410 10.450769 10.452221 10.456128 10.459906 10.460760 10.461719
#> [4208] 10.461750 10.464112 10.464918 10.467891 10.467993 10.473195 10.474428
#> [4215] 10.478586 10.479458 10.480860 10.482052 10.483738 10.484570 10.487935
#> [4222] 10.493587 10.498938 10.502908 10.503561 10.508532 10.508542 10.514160
#> [4229] 10.515737 10.521432 10.522742 10.523165 10.523901 10.526354 10.527426
#> [4236] 10.528604 10.528644 10.532220 10.533008 10.534114 10.534862 10.534994
#> [4243] 10.535009 10.536030 10.537415 10.538700 10.540155 10.540931 10.545637
#> [4250] 10.547217 10.548782 10.553396 10.554478 10.559361 10.560347 10.563557
#> [4257] 10.563928 10.566996 10.568366 10.571633 10.572606 10.574488 10.574598
#> [4264] 10.578974 10.583488 10.585373 10.585588 10.586177 10.591099 10.591806
#> [4271] 10.598304 10.604436 10.605871 10.606798 10.606803 10.607405 10.608311
#> [4278] 10.609894 10.609901 10.611055 10.622358 10.622399 10.624167 10.627757
#> [4285] 10.629319 10.635673 10.636466 10.639954 10.644700 10.646649 10.647908
#> [4292] 10.649271 10.652996 10.654541 10.655164 10.656141 10.658612 10.659592
#> [4299] 10.660970 10.660970 10.662377 10.663174 10.663759 10.667598 10.670132
#> [4306] 10.672500 10.682283 10.682956 10.687435 10.690153 10.695075 10.695931
#> [4313] 10.696622 10.701588 10.703610 10.703693 10.704285 10.704494 10.704718
#> [4320] 10.705582 10.710181 10.710516 10.714208 10.715435 10.716238 10.720157
#> [4327] 10.720728 10.722593 10.725960 10.726785 10.728596 10.728827 10.729235
#> [4334] 10.733981 10.734493 10.737707 10.742082 10.745358 10.748193 10.751371
#> [4341] 10.752789 10.756202 10.758254 10.766979 10.771950 10.774237 10.782513
#> [4348] 10.788002 10.788886 10.789717 10.793972 10.800952 10.809061 10.821918
#> [4355] 10.822335 10.826138 10.831819 10.835002 10.837114 10.840191 10.841656
#> [4362] 10.843256 10.848288 10.849456 10.849612 10.853634 10.854301 10.861135
#> [4369] 10.864723 10.867602 10.868945 10.872964 10.874356 10.874507 10.887150
#> [4376] 10.890687 10.891358 10.894794 10.898308 10.898365 10.902254 10.905257
#> [4383] 10.905496 10.909405 10.914962 10.919727 10.923175 10.924205 10.929363
#> [4390] 10.930282 10.930462 10.938190 10.940186 10.940761 10.947552 10.948954
#> [4397] 10.951606 10.952555 10.955321 10.957657 10.961918 10.963472 10.963712
#> [4404] 10.969143 10.970116 10.970986 10.971998 10.972223 10.973623 10.978184
#> [4411] 10.978406 10.979551 10.979633 10.980023 10.984810 10.988237 10.988956
#> [4418] 10.989230 10.991767 10.991924 10.992300 10.993637 10.996427 10.999757
#> [4425] 11.004371 11.006225 11.006511 11.013627 11.018585 11.019798 11.020588
#> [4432] 11.024872 11.025874 11.026053 11.028204 11.029016 11.032029 11.034168
#> [4439] 11.036147 11.037770 11.041080 11.045090 11.046019 11.048393 11.051006
#> [4446] 11.051262 11.056077 11.056421 11.057590 11.057759 11.058906 11.063091
#> [4453] 11.063170 11.065312 11.065900 11.066806 11.067062 11.067252 11.068355
#> [4460] 11.071273 11.072304 11.073459 11.077677 11.083747 11.085778 11.089386
#> [4467] 11.089878 11.090648 11.091586 11.093234 11.098722 11.099048 11.099580
#> [4474] 11.108721 11.108747 11.109649 11.114041 11.115680 11.117351 11.118721
#> [4481] 11.120154 11.122118 11.122282 11.124738 11.135602 11.137776 11.141009
#> [4488] 11.143614 11.145991 11.157549 11.161706 11.162923 11.163600 11.167257
#> [4495] 11.168791 11.177382 11.184512 11.184974 11.196513 11.198416 11.200446
#> [4502] 11.202958 11.204594 11.207294 11.209351 11.217086 11.221434 11.223337
#> [4509] 11.224949 11.228069 11.230575 11.235730 11.235887 11.236718 11.237924
#> [4516] 11.239569 11.240972 11.243549 11.244986 11.247141 11.247250 11.247692
#> [4523] 11.247866 11.249847 11.253076 11.257268 11.259238 11.260076 11.263112
#> [4530] 11.266119 11.269382 11.270477 11.274219 11.275643 11.278169 11.278541
#> [4537] 11.279057 11.279312 11.279820 11.284165 11.287084 11.292197 11.292590
#> [4544] 11.300760 11.301968 11.302488 11.304756 11.305724 11.307220 11.309853
#> [4551] 11.312361 11.314563 11.318427 11.318753 11.320000 11.325427 11.327887
#> [4558] 11.328146 11.328691 11.328770 11.331131 11.331563 11.336191 11.337516
#> [4565] 11.338852 11.338896 11.339144 11.341784 11.344996 11.345662 11.348303
#> [4572] 11.351301 11.352925 11.353358 11.357144 11.358464 11.360219 11.360581
#> [4579] 11.362040 11.365591 11.367836 11.375187 11.377415 11.378337 11.379210
#> [4586] 11.381056 11.381352 11.384458 11.386576 11.388911 11.391821 11.393077
#> [4593] 11.398532 11.399726 11.401459 11.401681 11.402035 11.403386 11.403847
#> [4600] 11.407597 11.409065 11.411440 11.414403 11.417345 11.421109 11.422106
#> [4607] 11.422653 11.424128 11.426708 11.426956 11.428707 11.429329 11.430811
#> [4614] 11.432747 11.433551 11.437985 11.444201 11.445487 11.447688 11.450083
#> [4621] 11.450550 11.454811 11.458236 11.459917 11.460060 11.466345 11.472361
#> [4628] 11.472466 11.475011 11.479812 11.480963 11.481857 11.484990 11.486015
#> [4635] 11.491311 11.491403 11.492211 11.494467 11.496590 11.498340 11.499447
#> [4642] 11.500359 11.509260 11.513596 11.514489 11.514921 11.517323 11.519839
#> [4649] 11.523696 11.525505 11.531645 11.533401 11.535254 11.536837 11.541014
#> [4656] 11.541492 11.544822 11.545551 11.546545 11.549415 11.550421 11.551372
#> [4663] 11.556184 11.563203 11.571790 11.574066 11.577397 11.587722 11.591075
#> [4670] 11.599223 11.600368 11.605090 11.609381 11.612327 11.613667 11.613781
#> [4677] 11.614312 11.617022 11.618729 11.620433 11.624660 11.625050 11.627240
#> [4684] 11.637257 11.639939 11.640818 11.641548 11.648764 11.660642 11.672450
#> [4691] 11.676506 11.678203 11.680322 11.680360 11.681762 11.683323 11.686791
#> [4698] 11.688022 11.688160 11.688587 11.692677 11.700382 11.710641 11.715423
#> [4705] 11.715489 11.716721 11.717599 11.719236 11.725878 11.737965 11.738004
#> [4712] 11.742643 11.743243 11.746898 11.748710 11.749338 11.758412 11.766104
#> [4719] 11.771048 11.771361 11.775742 11.776224 11.780382 11.787168 11.792205
#> [4726] 11.797009 11.798444 11.802470 11.802667 11.804133 11.817562 11.820178
#> [4733] 11.822497 11.831859 11.834296 11.834833 11.838525 11.840301 11.840315
#> [4740] 11.842997 11.843467 11.843558 11.851684 11.853194 11.855273 11.861929
#> [4747] 11.872615 11.877483 11.877573 11.879211 11.880298 11.881269 11.886916
#> [4754] 11.888175 11.902479 11.903173 11.909879 11.913872 11.919066 11.923421
#> [4761] 11.927405 11.935725 11.936234 11.950549 11.957204 11.963492 11.966329
#> [4768] 11.986291 11.990748 11.991077 12.001350 12.001743 12.005356 12.008298
#> [4775] 12.017622 12.028344 12.035034 12.042043 12.048456 12.052073 12.056437
#> [4782] 12.059570 12.063322 12.068281 12.070352 12.070577 12.082273 12.082967
#> [4789] 12.085518 12.086100 12.088971 12.098711 12.107430 12.122263 12.132015
#> [4796] 12.137201 12.141437 12.148451 12.149375 12.158113 12.158346 12.161799
#> [4803] 12.167044 12.171924 12.172726 12.173790 12.174284 12.176502 12.178489
#> [4810] 12.197180 12.199251 12.200980 12.203131 12.207273 12.207598 12.211898
#> [4817] 12.212927 12.219003 12.240143 12.240285 12.240861 12.243857 12.255304
#> [4824] 12.260990 12.262418 12.276550 12.277482 12.291796 12.292588 12.294630
#> [4831] 12.314815 12.317355 12.326177 12.327374 12.342345 12.350669 12.351836
#> [4838] 12.375668 12.379056 12.386606 12.389054 12.410890 12.418940 12.419641
#> [4845] 12.425325 12.425995 12.440486 12.443578 12.446519 12.446599 12.454561
#> [4852] 12.461883 12.463344 12.463938 12.481747 12.485331 12.490183 12.491598
#> [4859] 12.503590 12.507888 12.520613 12.521139 12.522168 12.534145 12.548851
#> [4866] 12.551082 12.566201 12.581081 12.592424 12.594357 12.595109 12.595621
#> [4873] 12.596749 12.628587 12.630808 12.643106 12.644029 12.645790 12.647467
#> [4880] 12.660878 12.664221 12.665761 12.674832 12.692051 12.711278 12.715471
#> [4887] 12.725209 12.776053 12.776616 12.783318 12.801744 12.832156 12.840253
#> [4894] 12.847851 12.865401 12.880416 12.902875 12.907756 12.918098 12.925044
#> [4901] 12.955311 12.978573 12.997181 13.001517 13.003515 13.006015 13.017714
#> [4908] 13.035540 13.058672 13.065435 13.082855 13.101279 13.116223 13.120064
#> [4915] 13.124714 13.127848 13.139090 13.167129 13.170324 13.178371 13.188077
#> [4922] 13.240804 13.263234 13.365053 13.370910 13.372890 13.379580 13.379903
#> [4929] 13.386453 13.448301 13.452906 13.690780 13.708035 13.740336 13.757435
#> [4936] 13.765723 13.768802 13.771284 13.812258 13.819379 13.870103 13.957837
#> [4943] 13.973610 13.991683 14.020244 14.066920 14.179179 14.235405 14.241133
#> [4950] 14.244884 14.354039 14.388138
dat <- dat %>% mutate(temp = ifelse(quarter == 1, NA, temp))
#> mutate: changed 5,123 values (60%) of 'temp' (5123 new NA)
sort(unique(filter(dat, quarter == 1)$temp))
#> filter: removed 3,447 rows (40%), 5,123 rows remaining
#> numeric(0)Add back in the data that get environmental variables added
fishdat2 <- fishdat %>% filter(!year %in% unique(dat$year))
#> filter: removed 8,597 rows (96%), 342 rows remaining
sort(unique(fishdat2$year))
#> [1] 1992 2020
sort(unique(dat$year))
#> [1] 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
#> [16] 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
dat <- bind_rows(dat, fishdat2)
sort(unique(dat$year))
#> [1] 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
#> [16] 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
dat %>% group_by(year, quarter) %>% summarise(mean_temp = mean(temp)) %>% as.data.frame()
#> group_by: 2 grouping variables (year, quarter)
#> summarise: now 58 rows and 3 columns, one group variable remaining (year)
#> year quarter mean_temp
#> 1 1992 1 NA
#> 2 1992 4 NA
#> 3 1993 1 NA
#> 4 1993 4 7.265573
#> 5 1994 1 NA
#> 6 1994 4 8.127241
#> 7 1995 1 NA
#> 8 1995 4 8.445461
#> 9 1996 1 NA
#> 10 1996 4 8.302044
#> 11 1997 1 NA
#> 12 1997 4 8.489010
#> 13 1998 1 NA
#> 14 1998 4 7.368595
#> 15 1999 1 NA
#> 16 1999 4 8.485449
#> 17 2000 1 NA
#> 18 2000 4 8.083449
#> 19 2001 1 NA
#> 20 2001 4 8.072406
#> 21 2002 1 NA
#> 22 2002 4 8.757268
#> 23 2003 1 NA
#> 24 2003 4 8.481996
#> 25 2004 1 NA
#> 26 2004 4 8.530806
#> 27 2005 1 NA
#> 28 2005 4 7.689341
#> 29 2006 1 NA
#> 30 2006 4 8.108078
#> 31 2007 1 NA
#> 32 2007 4 8.130461
#> 33 2008 1 NA
#> 34 2008 4 8.416102
#> 35 2009 1 NA
#> 36 2009 4 8.943075
#> 37 2010 1 NA
#> 38 2010 4 6.386677
#> 39 2011 1 NA
#> 40 2011 4 7.317723
#> 41 2012 1 NA
#> 42 2012 4 7.963451
#> 43 2013 1 NA
#> 44 2013 4 7.469514
#> 45 2014 1 NA
#> 46 2014 4 9.231226
#> 47 2015 1 NA
#> 48 2015 4 8.398530
#> 49 2016 1 NA
#> 50 2016 4 9.290638
#> 51 2017 1 NA
#> 52 2017 4 8.376726
#> 53 2018 1 NA
#> 54 2018 4 9.602791
#> 55 2019 1 NA
#> 56 2019 4 8.319802
#> 57 2020 1 NA
#> 58 2020 4 NAAdd UTM coords
# First add UTM coords
# Add UTM coords
# Function
LongLatToUTM <- function(x, y, zone){
xy <- data.frame(ID = 1:length(x), X = x, Y = y)
coordinates(xy) <- c("X", "Y")
proj4string(xy) <- CRS("+proj=longlat +datum=WGS84") ## for example
res <- spTransform(xy, CRS(paste("+proj=utm +zone=",zone," ellps=WGS84",sep='')))
return(as.data.frame(res))
}
utm_coords <- LongLatToUTM(dat$lon, dat$lat, zone = 33)
#> Warning in showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj =
#> prefer_proj): Discarded datum Unknown based on WGS84 ellipsoid in CRS definition
dat$X <- utm_coords$X/1000 # for computational reasons
dat$Y <- utm_coords$Y/1000 # for computational reasonsMake Gifs
Save data
write.csv(dat, file = "data/for_analysis/mdat_cpue_q_1_4.csv", row.names = FALSE)